TWI808435B - Multi-view analysis in automated testing apparatus - Google Patents

Abstract

Provided is a multi-view analysis in automated testing apparatus. The device can include a receiving mechanism to receive a carrier. The carrier may include a holding area. The device may include a camera module arranged to capture a plurality of images, including a first image and a second image, of the holding area. The device may include a positioning mechanism operable to adjust a relative location of the carrier to the camera. A processor in the device may utilize the camera module to: identify an edge of the first image; cause the positioning mechanism to adjust the relative location of the carrier to the camera in a manner such that, when the camera takes the second image, an edge of the second image aligns with the identified edge of the first image; and perform a set of analytic processes on a combined image from the first and second images.

Description

Automatic test device for analysis of complex viewing angles

The present invention relates to an automatic test device for analysis of multiple viewing angles, which can be used for testing biological samples; more particularly, it relates to a test device with amplifying function or analyte quantification function.

Currently, the testing of liquid inclusions is usually entrusted to professional testing institutes using expensive microscope equipment with high magnification ratios to perform the tests. Since ordinary people do not have a microscope device, testing activities cannot be performed by ordinary people.

However, in some of today's testing categories there is a need to perform periodic testing; thus creating an excessive burden in terms of time and expense for requirements that require frequent testing. For example, the category of long-term testing includes semen testing of infertile patients. The semen test mainly performs observations on the number of sperm, their motility and morphology.

The semen test method comprises: standing the semen of a male subject at room temperature for a period of time, obtaining a drop of the sample, instilling the sample on a glass slide, and observing the sample under a microscope. These observations include not only high-magnification observations of individual spermatozoa to identify the external appearance of individual spermatozoa, but also observations of a large number of total spermatozoa, their motility, morphology, and number per unit area. However, individuals cannot perform semen tests themselves because the industry has not yet developed technology that allows individuals to perform tests via simple assistive devices.

The present invention discloses methods, devices and systems for testing biological samples. In an example aspect, an automated testing device for testing multiple view angle analysis of a biological sample is disclosed. The device includes a receiving mechanism to receive a carrier including a holding area configured to carry a biological sample.

The device includes a camera module configured to capture an imagery of the holding area and a processor configured to identify visual cues on a carrier from the captured imagery of the holding area using the camera module and to execute a set of analytical processing procedures on the captured imagery based on the identification of the visual cues. The identifying of the aforementioned visual cue further includes verifying whether the holding region carries the biological sample based on the manner in which the visual cue is displayed in the captured set of images, and selectively causing the processor to execute the analysis process on the captured set of images according to the result of the verification. In another example aspect, an automated test device for testing multiple view angle analysis of a biological sample includes a receiving mechanism to receive a carrier including a holding area configured to carry or have been exposed to a biological sample. The device includes a camera module configured to capture multiple images of the holding area, and a processor configured to use the camera module to adaptively select an analysis algorithm suitable for movement characteristics of the biological sample to be measured based on the multiple images of the holding area and execute a set of analysis processing programs corresponding to the selected analysis algorithm through the captured multiple images to generate an analysis result about the biological sample.

In another example aspect, an automated test device for testing multiple view angle analysis of a biological sample includes a receiving mechanism to receive a carrier including a holding area configured to carry or have been exposed to the biological sample. The device includes a camera configured to capture a plurality of images of the holding area including a first image, a second image. The device also includes a positioning mechanism operable to adjust the relative position of the carrier to the camera and a processor configured to identify, with the camera module, edges of the first image, the positioning mechanism to adjust the relative position of the carrier to the camera such that when the camera acquires a second image, the edges of the second image align with the identified edges of the first image, and to perform a set of analytical processing procedures on the image combined from the first and second images to determine one or more characteristics of the biological sample.

In another example aspect, an automated test device for testing multiple view angle analysis of a biological sample includes a receiving mechanism to receive a carrier including a holding area, wherein the holding area carries the biological sample or has been exposed to the biological sample. The device includes a camera module configured to capture a collective image of the holding area. The camera module further includes a focus motor operable to adjust the focus of the camera. The device further includes a processor configured to utilize the camera module to determine volumetric properties of the holding region based on operation of the focus motor, and to execute a set of analytical processing procedures on at least a portion of the captured set of images of the holding region to determine one or more properties of the biological sample. One or more properties of the biological sample receive processor adjustments based on the determined holding region volume properties.

These and other features of the technology will be described in this document.

5: Test strip

10: carrier

11: Sample holding area

12: Sample receiving port

13: Air channel

14: Protruding parts

15: Flexible transparent film

16: Beam auxiliary guiding structure

20: outer cover

21: Groove

30: Enlarge parts

30B: Enlarge parts

30C: Enlarging Parts

31: Enlarge parts

40: sample

42: Sample collection sheet

42A: Sample collection area

50: side lighting device

60:Smart communication device

61: camera

70:Instrument device

71: Lower barrel base

72: Upper barrel main body

73:Insert port

74: magnifying lens

75: Assembling the frame

76:Camera Alignment Hole

80: light source

92: Anti-slip film

94: pH test paper

96: Release paper

98: Isolation components

1505: step

1510: step

1515: step

1520: step

1525: step

1530: step

1540: step

1545: step

1550: step

1555: step

1605: step

1610: step

1615: step

1620: step

1625: step

1630: step

1705: sperm

1710: track

1720: track

1805: track

1810: Curve speed

1815: Linear speed

1820: Amplitude of lateral head displacement

1825: Average path

1900: Test equipment

1905: Test strip device

1910: Collection bottle

1920: screen

2000: Test device

2005: Test strip device

2105: Test strip device

2110: Magnification components

2115: Sample holding area

2130: Camera module

2135: lens

2140: light source

2205: Test strip device

2210A: outer cover

2210B: Magnification component

2215A: The first holding area

2215B: Second holding area

2230A: The first camera module

2230B: Second camera module

2240A: light source

2240B: light source

2510: Collection bottle

2550: switch

2560: motor

2570: camera

2610: Collection bottle

2660: motor

2680: Move components

2690: Light Sensor

2905(1): Carriers

2905(2): Carrier

2905(3): Carriers

2905(4): Carriers

2915A: The first holding area

2915B: Second holding area

3000: handler

3002: step

3004: step

3006: step

3008: step

3010: step

3012: Step

3014: Step

3105: carrier

3117(1): Visual signs

3117(2): Visual signs

3117(3): Visual signs

3117(4): Visual signs

3117(5): Visual signs

3115B: holding area

3200: Handler

3202:step

3204:step

3206:step

3208:step

3210:step

3212:step

3300: handler

3310:step

3320:step

3330:step

3340:step

3342:step

3344:step

3346:step

3350:step

3402: block

3510: Candidate block

3700: Calibration handler

3710:step

3720:step

3730:step

3740:step

3742:step

3744:step

3746:step

3750:step

4102: Test particles

4300: Handler

4310:step

4320:step

4330:step

4342:step

4346:step

4601: small area

4700: handler

4710:step

4720:step

4730:step

4800: Handler

4810:step

4820:step

4830:step

4840:step

4901: Plural axis of platform

5210: outer cover

5217a: First visual cue

5217b: Second visual cue

5220: carrier

5230: camera module

A1: Automatic test device

A2: Automatic test device

A3: Automatic test device

A4: Automatic test device

A5: Automatic test device

A6: Automatic test device

A7: Automatic test device

A8: Automatic test device

A9: Automatic test device

A10: Automatic test device

H1: focal length parameter

H2: focal length parameter

L1: Arrow

L2: Arrow

L3: Arrow

S110: step

S120: step

S130: step

S140: step

FIG. 1A is an exploded view of an automatic test device for complex view analysis according to an embodiment of the present invention.

FIG. 1B is an assembled view of the testing device of FIG. 1A .

Figure 2A is a cross-sectional view of the testing device of Figure 1A.

Figure 2B is a cross-sectional view of another embodiment of a testing device.

FIG. 3 is a flow chart of the testing of the testing device according to an embodiment of the present invention.

FIG. 4 is a cross-sectional view of an automatic test device for complex viewing angle analysis according to another embodiment of the present invention.

FIG. 5 is a cross-sectional view of an automatic test device for complex viewing angle analysis according to another embodiment of the present invention.

FIG. 6 is a schematic diagram of the testing device of FIG. 5 in use.

FIG. 7 is a schematic diagram of an automatic test device for complex view analysis according to another embodiment of the present invention.

FIG. 8 is a schematic diagram of an automatic test device for complex viewing angle analysis according to another embodiment of the present invention.

FIG. 9 is a schematic diagram of an automatic test device for complex viewing angle analysis according to another embodiment of the present invention.

FIG. 10 is a schematic diagram of an automatic test device for complex viewing angle analysis according to another embodiment of the present invention.

FIG. 11 to FIG. 13 are views of an automatic test device for analyzing multiple viewing angles according to another three specific examples of the present invention.

14A is a schematic diagram of a test strip inserted into a meter device according to another embodiment of the present invention.

14B is a schematic diagram of components of an instrumentation device according to another embodiment of the present invention.

FIG. 15A shows a sample processing procedure for a semen test performed by a device such as a meter device or a smart communication device.

Figure 15B shows a sample step 1515 of the process shown in Figure 15A.

Figure 15C shows sample steps 1520 of the process shown in Figure 15A.

Figure 15D shows sample steps 1530 of the process shown in Figure 15A.

Figure 15E shows sample steps 1550 of the process shown in Figure 15A.

Figure 15F shows a sample step 1555 of the process shown in Figure 15A.

Figure 16 shows a sample processing procedure for determining sperm concentration.

Fig. 17 shows the sample sperm and the track of the sample sperm.

Fig. 18 shows the sample processing procedure for determining sperm trajectory and motility.

Figure 19 is a schematic diagram of a test setup including a collection vial.

Figure 20 is a schematic diagram of the test setup excluding the collection bottle.

21B and 21C are schematic cross-sectional views of various embodiments of testing devices.

22 is a schematic cross-sectional view of a test device with a test strip device having two sample holding areas.

Fig. 23 is a schematic diagram of components of a testing device with autofocus function.

Fig. 24 is a schematic diagram of components of another testing device with autofocus function.

Fig. 25 is a schematic cross-sectional view of a testing device including a switch and a motor.

Fig. 26 is a schematic cross-sectional view of a testing device including a flexible element.

27 is a flowchart of a process for analyzing a semen sample from a male client or patient.

Figure 28 is a flowchart of a process for analyzing LH or HCG of a female client or patient.

FIG. 29 shows an example of a carrier that may be suitable for a test device with a multi-camera setup, such as the test device shown in FIG. 22 .

30 is a flowchart of a process for analyzing the fertility of both male and female subjects using the test devices disclosed herein.

Figure 31 shows an additional example of a carrier having a visual cue (eg, in or near the holding area) can be used for an analytical process performed with a control test device.

32 is a flowchart of an additional example of a process that may be implemented by the disclosed test device to adaptively execute an analysis process based on visual cues.

33 is an example flow diagram of a process routine that may be implemented by the disclosed testing device.

Fig. 34 is an example image where the holding area is divided into many blocks.

FIG. 35 is an example image illustrating a selection process of a part of candidate blocks.

Fig. 36 is an example image illustrating an image processing procedure (eg, polarization) and the result after cell number determination.

Figure 37 is a flowchart of an example calibration routine that may be implemented by the disclosed testing device.

Figure 38 Test carrier carries example images of visual cues and/or graphic patterns that may be used to calibrate or validate a test device.

FIG. 39 is an example image of the visual cue in FIG. 38 captured by the disclosed test device.

40A and 40B illustrate different image qualities for different blocks in the captured image of FIG. 39 .

Figure 41 is an example image of a test carrier carrying a test sample that may be used to calibrate or validate a test device.

42A and 42B illustrate different image qualities for different blocks in the captured image of FIG. 41 .

43 is an example flow diagram of a process procedure that may be implemented by a test device disclosed herein to verify that a sample holding region carries a biological sample.

Figure 44A shows an example of a captured image of an empty or dry sample holding area.

Figure 44B shows another example of a captured image of an empty or dry sample holding area.

Figure 45A shows an example of a captured image of a sample holding region loaded with biological sample-carrying fluid.

45B shows another example of a captured image of a sample holding region loaded with biological sample-carrying fluid.

Figure 46 shows an example image including many misclassified regions.

FIG. 47 is an example flow chart of a processing procedure for determining the movement characteristics of a sample by the testing device of the present invention.

48 is an example flow diagram of a process that may be implemented by the test apparatus disclosed herein to utilize multiple fields of view to improve results.

Figure 49 illustrates an exemplary multi-axis mobile platform.

FIG. 50A shows an example manner in which images are sequentially acquired clockwise as viewed from the camera.

FIG. 50B shows an example manner in which images are sequentially acquired in a progressive scan.

FIG. 51A shows an example of a preset position of an adjustable lens of a camera module.

FIG. 51B shows the camera module of FIG. 51A with the lens in an extended position.

Fig. 52 shows an example of a configuration for determining the actual volume of a sample contained in a carrier.

1A and 1B illustrate an automatic testing device for testing biological samples for multi-view analysis according to an embodiment of the present invention. The specific examples disclosed herein are for illustrative purposes and should not be considered as limitations on the invention as required. The automatic testing device A1 for multiple viewing angle analysis of testing biological samples comprises: a carrier 10 having a sample holding area 11 formed on the top of the carrier 10, an outer cover 20 stacked on the top of the carrier 10, and at least one magnifying part 30 (also referred to as a magnifying component or a magnifying glass) comprising a convex lens-type surface formed on the outer cover 20.

The magnifying component 30 of this embodiment includes a planar convex lens as shown in FIG. 1A. However, other types of magnification lenses (eg, double-sided lenticular lenses) may be included as the magnification member 30 . The magnification member 30 is arranged to align with and cover the sample holding area 11 of the carrier 10 . The amplification component 30 can have various amplification ratios based on the test requirements of various tests. For example, the tests may include semen tests, urine tests, synovial joint fluid tests, skin tests, water tests or other bodily fluid tests, among others.

The test using the automatic test device A1 for testing multiple viewing angles of biological samples of this embodiment does not require additional magnifying lenses or laboratory microscopes, which are expensive and time-consuming to operate. Furthermore, there is no need to align the sample holding area with the magnifying lens or laboratory microscope.

As shown in FIG. 1A , the sample holding region 11 of the carrier 10 may be formed with a recessed structure. The recessed structure design provides a stable and large storage space containing the sample 40 . The recessed structure allows the sample to rest for a desired period of time before performing the test. For example, before performing a motility test on a semen sample, it is necessary to allow the semen sample to rest at room temperature for a desired period of time prior to performing the motility test.

The sample 40 may first be dripped into the recessed structure (ie, the sample holding area 11 of the carrier 10 ) to stand for a period of time. As shown in FIG. 1B , the total area of the housing 20 may be smaller than the total area of the carrier 10 . A sample receiving port 12 exposed to the outside of the housing 20 is formed on one side of the sample holding area 11 . The sample receiving port 12 can be designed to have an outwardly flared shape, which can help to drip the sample smoothly.

FIG. 2A shows the air channel 13 extending beyond the other side of the housing 20 and formed on the other side of the sample holding area 11 . The air channel 13 prevents air from filling the interior of the sample holding area 11 which prevents the sample from being received when it is in a liquid state.

As shown in FIG. 2A , the side lighting device 50 may be disposed at one side of the carrier 10 of the automatic test device A1 . The side illuminator 50 can provide illumination for the sample 40 in the sample holding area 11 and thus improve the resolution of the captured test image of the sample 40 . In some embodiments, the sample holding area 11 can receive illumination from a light source on the top or bottom of the automatic testing device A1 .

As shown in FIG. 1A , the amplifying member 30 and the housing 20 may be integrally formed, that is, the amplifying member 30 and the housing 20 may be a single component. In other embodiments (such as the embodiment shown in FIG. 2B ), the detachable cover 20 and the upwardly facing concave part disposed in the detachable cover 20, that is, the placement in the groove 21 Large components 30 may each be separate components adapted to be integrated together. In other words, the same type of detachable housing 20 can be integrated with different magnification components 30 of various magnification ratios.

In some specific examples, the distance between the bottom of the detachable cover 20 and the sample holding area 11 is 0.005 mm to 10 mm. In some embodiments, the distance between the bottom of the detachable cover 20 and the sample holding area 11 is about 0.01 mm. The test device may include one or more spacers (not shown) to ensure the distance between the bottom of the detachable housing 20 and the sample holding area 11 . The spacer may be integrally formed with the removable cover 20 or the sample holding area 11 of the carrier 10 .

In some embodiments, the strip including carrier 10 and cover 20 is used for sperm testing. In some embodiments, the optimal angular magnification ratio for determining sperm concentration and motility is about 100 to 200. In some embodiments, the optimal angular magnification ratio for determining sperm morphology is about 200-300. The thinner the magnifying element, the higher the angular magnification ratio.

The focal length of the magnifying element can also be related to the angular magnification ratio. In some embodiments, a magnification element having an angular magnification ratio of 100 has a focal length of 2.19 mm. A magnification assembly with an angular magnification ratio of 156 has a focal length of 1.61 mm. A magnification element with an angular magnification ratio of 300 has a focal length of 0.73 mm. In some embodiments, the magnification assembly has an angular magnification ratio of at least 30, preferably at least 50. In some embodiments, the focal length of the magnification assembly is 0.1 mm to 3 mm.

FIG. 3 shows a sample processing procedure for performing a test using the automatic test device A1 shown in FIG. 1B for testing multiple view angle analysis of a biological sample. In step S110 , the sample 40 to be tested is placed in the sample holding area 11 . In step S110 , the cover 20 is stacked on top of the carrier 10 , and then the sample 40 to be tested is placed in the sample holding area 11 from the sample receiving port 12 . Alternatively, the sample 40 to be tested may first be placed directly in the sample holding area 11 , after which the housing 20 is stacked on top of the carrier 10 . In step S120, according to the test requirements of the sample 40, the sample 40 is placed in a static In the sample holding area 11, selectively last for a period of time. In step S130, a smart communication device (such as a mobile phone) is attached to the housing 20, and the camera of the mobile phone is aligned with the magnifying part 30, so as to use the camera of the mobile phone to capture an image or video of the sample through the magnifying part 30. In step S140, an application program (APP) running on a mobile phone or other analysis device can be used to perform analysis on the image or video to obtain test results.

As shown in FIG. 4 , a supporting side such as a protruding part 14 may be further formed at the boundary of the enlarging part 30 on the top of the outer cover 20 of the automatic testing device A2. In some embodiments, a protruding support structure can be formed on top of the housing 20 by adding protruding features 14 . When a user attempts to capture an image or video of a sample using the smart communication device 60 (e.g., a mobile device such as a smart phone or a single-board computer), one side of the smart communication device 60 with the camera 61 can be fixed to the protruding member 14 (in the direction shown by arrow L1). Therefore, the automatic testing device A2 allows the user to use the smart communication device 60 to capture images or videos of the samples, and does not require expensive testing devices to record the images or videos. In addition, for an optimum observation distance, the height of the protruding part 14 can be predetermined based on the specifications of the camera 61 and the automatic test device A2.

As shown in FIGS. 5 and 6 , the automatic test device A3 may include an instrumentation device 70 (also referred to as a base assembly). The meter device 70 includes a lower barrel base 71 and an upper barrel body 72 that can be raised or lowered relative to the lower barrel base 71 . The lower barrel base 71 has an insertion port 73 providing an insertion location for the housing 20 and carrier 10 stacked together. An upward light emitting device (also referred to as a light source) 80 is disposed on the bottom of the lower barrel base 71 to provide illumination to the combination of the housing 20 and the carrier 10 from the bottom. The upper barrel body 72 may include, for example, at least one additional magnifying lens 74 for further magnification.

The upper barrel body 72 may be attached to the lower barrel base 71 using a threaded mechanism such that the upper barrel body 72 may be raised or lowered relative to the lower barrel base 71 as a screw. In other words, the upper barrel body 72 is rotatable relative to the lower barrel base 71 in the arrow L2 direction so that the upper barrel body 72 moves upward and downward relative to the lower barrel base 71 in the arrow L3 direction. By adjusting the upper barrel main The height of the body 72 relative to the lower barrel base 71 , the system adjusts the height of the magnifying lens 74 (changing the magnification ratio) and the height of the camera 61 .

An assembly frame 75 (also referred to as a form fit frame) may be placed at the upper end of the upper barrel body 72 . The assembly frame 75 fixes the smart communication device 60 at a predetermined position. The assembly frame 75 has a camera alignment hole 76 . The camera 61 of the smart communication device 60 can receive light from the sample through the camera alignment hole 76 .

The camera 61 installed on the current smart communication device 60 typically only has a digital zoom function. In general, high-precision testing requires optical zoom lenses. However, a user using the automatic test device A3 does not need the camera 61 with an optical zoom lens. The height adjustment function of the automatic testing device A3 provides a flexible solution for aligning the sample, magnifying lens and camera 61 .

FIG. 6 shows the smart communication device 60 assembled and secured to the assembly frame 75 which rests on the upper barrel body 72 . The housing 20 and the carrier 10 containing the sample 40 are inserted through the insertion port 73 . The upward light emitting device 80 can provide illumination to the sample and increase the brightness of the sample.

The upper barrel body 72 or the gauge device 70 can be rotated along the direction L2 to adjust the height of the magnifying lens 74 and the camera 61 upwards or downwards along the direction L3. The height adjustment mechanism realizes the function of adjusting the magnification ratio. The camera 61 can capture a dynamic video or a static test image of the sample 40 after zooming in. In addition, the smart communication device 60 can use its original equipment functions to store captured video or images, transmit test images or videos, and perform subsequent processing.

As shown in FIG. 7 , the automatic test device A4 for multiple view analysis of testing biological samples includes a plurality of magnification components 30 , 30B, 30C with different magnification ratios disposed on the housing 20 . The user can shift the housing 20 to align the sample holding area 11 of the carrier 10 with any of the magnification components 30, 30B, 30C having different magnification ratios in order to obtain test results having different magnification ratios. With this design, the automatic test device A4 with the amplification function of a single module can be applied to meet the amplification requirements of multiple test protocols without changing the amplification components or the housing.

As shown in FIG. 8 , the automatic testing device A5 for testing biological samples for multi-view analysis includes a flexible transparent film 15 . The flexible transparent film 15 is disposed between the carrier 10 and the magnifying component 30 and covers the sample holding area 11 . The flexible transparent film 15 covers the sample 40 (in liquid state) such that the sample 40 is in a confined space. Therefore, external influences caused by air, dust and dirt are kept to a minimum. In addition, the automatic testing device A5 can adjust the focal length by changing the thickness of the flexible transparent film 15 .

As shown in FIG. 9 , the magnifying part 30 of the automatic testing device A6 for testing multiple viewing angles of biological samples is a planar convex lens, and the surface of the magnifying part 30 facing the carrier 10 is a protruding surface. Accordingly, an upwardly concave hollow part, ie, a groove 21 is formed at the surface of the enlarged part 30 facing the carrier 10 . The focal length parameter H1 is defined by the thickness of the thickest part of the magnifying part 30 of the planar convex lens. As shown in FIG. 10 , the focal length parameter H2 of the automatic test device A7 for testing the multiple viewing angle analysis of biological samples is different from the focal length parameter H1 of FIG. 9 .

The focal lengths H1 and H2 can be adjusted by changing the thickness of the cover 20 or the curvature of the magnifying part 30 . For example, the focal length H2 shown in FIG. 10 is greater than the focal length H1 shown in FIG. 9 , and is achieved by changing the curvature of the magnifying part 30 . In this way, testing requirements for various focal lengths can be met by using different magnifying components 30 .

In some embodiments, magnification member 30 may be transparent and the remainder of housing 20 may be opaque. In addition, the carrier 10 may include a transparent sample holding area 11 . The remainder of the carrier 10 may be opaque. When performing a test operation on the test device, light can propagate through the sample holding area 11, the amplifying component 30 to suppress the chance of light interference in other parts of the device.

Referring to FIG. 11 , in the automatic testing device A8 for multiple viewing angle analysis of biological samples, the carrier 10 of the automatic testing device A8 further includes an auxiliary beam guiding structure 16 formed at the bottom surface of the carrier 10 . The carrier 10 can be made of transparent or translucent material. The beam assist guiding structure 16 may be opaque or include a grained structure, rough pattern, engraved pattern, or scattering to reach the guiding junction. Other suitable configurations for the beam of configuration 16. The auxiliary beam guiding structure 16 can provide a specific pattern on the entire surface or a part of the surface of the cover and the carrier. The auxiliary beam guiding structure 16 can also be formed entirely around the side surface of the carrier 10 .

When the housing 20 and carrier 10 are stacked and attached to the smart communication device 60 (eg, as shown in FIG. 4 ), the magnification member 30 is aligned with the camera 61 of the smart communication device 60 . In addition, a supplementary light (not shown) can be placed near the camera 61 on the surface of the smart communication device 60 . A beam of light provided by supplemental light can be directed to the carrier 10 to illuminate the sample holding area 11 through the housing 20 . At the same time, the light beam auxiliary guiding structure 16 of the carrier 10 can scatter the light beam provided by the supplementary light, thereby improving the brightness and illumination uniformity of the sample holding area 11 .

By installing the light beam auxiliary guiding structure 16 , the testing device does not require an additional supplementary light source to illuminate the carrier 10 . Therefore, the cover 20 includes a light-transmitting material so that the supplementary light of the smart communication device 60 can pass through the cover 20 to reach the sample. In some alternative embodiments, the device does not include housing 20 and the supplemental light reaches carrier 10 directly without propagating through housing 20 .

The automatic test device A8 for testing multiple viewing angles of biological samples may include a non-slip film 92 , a release paper 96 and a pH test paper 94 . A non-slip film 92 is attached on the supporting side of the housing 20, such as the top side, and is used to stably seat the housing 20 to the camera 61 of the smart communication device 60, as shown in FIG. Using the anti-slip film 92, the positioning of the smart communication device 60 relative to the automatic test device A8 is fixed to a predetermined structure.

The non-slip film 92 may have an opening aligned with the magnifying member 30 so that the non-slip film 92 does not block the transmission of light from the sample to the camera 61 through the magnifying member 30 . The anti-slip film 92 can include, for example, silicon material, and the surface of the anti-slip film 92 can be protected by using the release paper 96 to maintain the stickiness of the paper. A pH test paper 94 can be placed on the sample holding area 11 of the carrier 10 to provide an indication of the pH value of the sample. The pH paper 94 can be replaced after use.

In addition, the magnifying component 30 and the cover 20 can adopt a detachable design. Therefore, the user may select another amplifying component 31 different from the amplifying component 30 to replace the original amplifying component 30 based on testing requirements. Various magnification components that may be assembled with housing 20 are assembled to achieve different magnification ratios or other optical characteristics.

Referring now to FIG. 12 , the automatic testing device A9 for testing multiple viewing angles of biological samples may further include a sample collection sheet 42 disposed in the sample holding area 11 . Sample collection sheet 42, for example, has a sample collection area 42A. The sample collection area 42A may collect sperm, subcutaneous tissue/cells, parasite eggs, and similar solid test subjects using adhesives or other methods. In some embodiments, the sample collection sheet 42 can serve as a spacer to maintain the distance between the housing 20 and the sample holding area 11 .

Next, referring to FIG. 13 , the automatic testing device A10 for testing multiple viewing angles of biological samples may include an isolation component 98 disposed at the sample holding area 11 between the carrier 10 and the housing 20 . The isolation component 98 can isolate the amplifying part 30 from the test liquid in the sample holding area 11 and prevent the test liquid from polluting the amplifying part 30 . In some embodiments, the isolation assembly 98 can be used as a spacer to maintain the distance between the housing 20 and the sample holding area 11 . Isolation assembly 98 may be integrated with housing 20 as a single assembly. Alternatively, isolation component 98 may be integrated with carrier 10 as a single component.

14A is a schematic diagram of a test strip inserted into a meter device according to another embodiment of the present invention. The test strip 5 (also called a test cartridge) includes a detachable cover 20 and a carrier 10 . In other words, the combination of the removable cover 20 and the carrier 10 (eg, as shown in FIG. 1B ) forms the test strip 5 . The test strip 5 is inserted into the meter device 70 (also referred to as the base assembly) via the insertion port. The insertion ports may be, for example, lateral or vertical insertion ports. Meter device 70 may include, for example, components for capturing images of samples collected in test strip 5 .

14B is a schematic diagram of components of an instrumentation device according to another embodiment of the present invention. Meter device 70 includes an insertion port 73 that provides an insertion location for test strip 5 . The test strip 5 includes a carrier 10 and a detachable cover 20 . The detachable housing includes an enlargement member 30 . Meter unit 70 includes a Camera 61 for image or video of the sample holding area of carrier 10 . The camera 61 is aligned with the magnification part 30 . The instrumentation device further comprises a light source 80 for illuminating the sample holding area from the bottom. In some embodiments, a collimator (eg, a collimator lens or a light reflector; now shown) can be placed on top of the light source 80 for collimating the light beam. An annular aperture can further be placed between the light source 80 and the collimator so that the light beam traveling through the collimator forms a hollow cone-shaped light beam. The carrier 10 may comprise a transparent or translucent material for light transmission.

In some embodiments, instrumentation device 70 may further include a phase plate that shifts the phase of light emitted from the sample holding region. The speed of light increases or decreases as it travels through the sample. Thus, the rays that propagate through the sample are out of phase (approximately 90 degrees) from the remaining rays that do not travel through the sample. The out-of-phase light rays interfere with each other and enhance the contrast between bright and dark portions of the sample image.

The phase plate can further shift the phase of the light propagating through the sample by about 90 degrees in order to further enhance the contrast caused by the interference of light out of phase. Thus, the light rays propagating through the sample are approximately 180 degrees out of phase with the remaining light rays not propagating through the sample. This destructive interference between light rays enhances the contrast of the sample image by darkening objects in the image and brightening the boundaries of those objects.

In some alternative embodiments, this phase plate may be placed on top of the removable housing 20 of the test strip 5 . In other words, the phase plate may be part of the test strip 5 rather than the instrumentation device 70 .

Fig. 15 shows a sample processing procedure for a semen test by a device such as the meter device 70 or the smart communication device 60 shown in Fig. 5 and Fig. 14 respectively. In step 1505, the device obtains an image (frame) of the sample. In step 1510, the device determines sperm concentration based on the image. In step 1515, the device can further determine the pH value of the sample by analyzing the color or gray scale of the pH strip. For example, a device may include a processor to identify the color of a portion of an image captured by a camera (corresponding to a pH strip) and determine a biochemical characteristic (eg, pH level) of a biological sample contained in the strip. In some other embodiments, the light source of the device can provide illumination having at least one color. For example, The light source may include light emitters of different colors (eg, red, green, and blue) to form various colors of light. The camera of the device may further capture at least one (or more) images of the sample illuminated with light. The processor can compare the color of specific regions of the image (eg, pH strip regions) to determine the identity of the biological sample or the quantification of an analyte. In some embodiments, the processor only needs the color of a specific region of an image to determine the identity of the biological sample. For example, a device (eg, a test device) may include a color correction module for correcting the color of an image. The processor then analyzes the rectified image to determine characteristics of the biological sample. Alternatively, the test strip may include color corrected areas of known colors. The processor performs a color correction operation on the image based on the color correction region, and then analyzes the corrected image to determine the identity of the biological sample or the quantification of the analyte. In some embodiments, reagents in a pH strip (or other type of biochemical test strip) react with the biological sample, after which specific regions of the image (eg, pH strip regions) show specific colors. In some embodiments, specific areas for color detection necessarily require magnification of the image captured by the camera. Thus, at least in some embodiments, there are no magnifying elements or supplements above certain regions of the strip used for color detection (eg, the pH strip region). For example, some types of biochemical test strips contain photochemical reagents. When the photochemical reagent reacts with a specific analyte in the biological sample, the reaction causes a color change in the sample-holding region of the strip. The processor can analyze the image of the test strip (captured by the camera) to detect color changes and quantify specific analytes in the biological sample. In addition, the device can determine sperm morphology (1520), sperm volume (1525) and total number of sperm (1530). In step 1540, the device acquires a series of frames of the sample. In steps 1545, 1550, and 1555, the device may determine sperm motility parameters based on sperm trajectories and determine sperm motility.

Figure 16 shows a sample processing procedure for determining sperm concentration. In 1605, a camera of meter device 70 or smart communication device 60 ("the device") as shown in Figures 5 and 14, respectively, captures a magnified image of the sperm sample. The captured image is the original image used to determine the concentration of sperm. The device then converts the digital color image into a digital grayscale image, and further divides the digital grayscale image into regions.

In step 1610, the device performs an adaptive bounded binary calculation for each region based on the mean and standard deviation of the gray value of that region. The goal of this adaptive bounded binary computation is to identify objects that will be candidates for sperm as foreground objects and the rest of the region as background.

Foreground objects in the image after the binary calculation may still include impurities that are not actually sperm. The impurities are smaller or larger than the sperm. The method may set upper and lower boundary values for the size of the sperm. In step 1615, the device performs a noise reduction operation on the image by removing impurities that are larger than the upper boundary value of the sperm or smaller than the lower boundary value of the sperm. After the noise reduction operation, the foreground objects in the image represent sperm.

The method counts the number of sperm in an image based on the head portion of the sperm. In steps 1620 and 1625, the device performs a distance transform operation to calculate the minimum distance between the foreground object and the background, and also identify the location of the local maximum. These positions are candidates for sperm head positions.

In step 1630, the device performs an ellipse fitting operation on each sperm candidate to reduce false positive candidates that do not have an elliptical shape and thus are not sperm heads. The device then counts the total number of remaining positive candidates for the sperm and calculates the concentration of the sperm based on the volume represented by the image. The volume can be, for example, the area of the captured sample holding area multiplied by the distance between the sample holding area and the bottom of the housing.

In some embodiments, the device can use multiple images of the sample and calculate concentration values based on the images, respectively. Then, the device calculates the average value of these concentration values to minimize the measurement error of sperm concentration.

Using a series of images (eg, video frames) of the sample, the device can further determine the trajectory and motility of the sperm. For example, FIG. 17 shows sample sperm such as sperm 1705 and sample sperm trajectories such as trajectories 1710 and 1720 .

Fig. 18 shows the sample processing procedure for determining sperm trajectory and motility. A camera of meter device 70 or smart communication device 60 ("the device") as shown in FIGS. 5 and 14, respectively, captures a series of images (eg, video frames) of the sperm sample. The device uses the captured series of images to determine parameters of sperm motility. To determine parameters of sperm motility, the device needs to track the trajectory of each sperm in the series of images.

The device converts a digital color image into a digital grayscale image. The device first identifies the location of the head of the sperm in the first image of the series (eg, using the method shown in Figure 16). The identified head position of the sperm in the first image is the initial position of the sperm trajectory to be tracked. In some embodiments, the device can use a two-dimensional Kalman filter to estimate the movement trajectory of the sperm.

In some embodiments, the two-dimensional Kalman filtering for tracking the sperm s _j with the measurement z _j ( k ) includes the following steps:

(k|k-1)及誤差共變數矩陣

(k|k-1)：

1: Calculate the predicted state

( k | k -1) and error covariate matrix

( k | k -1):

(k|k-1)、量測值z _j (k)及誤差共變數矩陣

(k|k-1)，計算經預測量測值

(k|k-1)、量測值殘差

(k)及殘差共變數矩陣

(k)：

2: Use Predicted State

( k | k -1), measured value z _j ( k ) and error covariate matrix

( k | k -1), computes the predicted measured value

( k | k -1), measurement residual

( k ) and residual covariate matrix

( k ):

(k) T

(k)-1

(k)<γ及∥

(k)∥/T

V _max，則計算卡爾曼過濾增益

(k)、經更新狀態估計值

(k|k)及經更新誤差共變數矩陣

(k|k)：

3: if

( k ) T

( k )-1

( k )< γ and ∥

( k )∥/ T

V _max , then calculate the Kalman filter gain

( k ), the updated state estimate

( k | k ) and the updated error covariate matrix

( k | k ):

為第j個精子的位置及速度的狀態。

為估計誤差的共變數矩陣，Q(k-1)為處理雜訊共變數矩陣，N(k)為白色位置雜訊向量之共變數矩陣，γ為閘極臨限值且V _max為最大可能精子速度。 ( k | k -1) represents the prediction of image k based on image k -1,

is the position and velocity of the jth sperm.

is the covariate matrix of estimation error, Q(k -1) is the covariate matrix of processing noise, N(k ) is the covariate matrix of white position noise vector, γ is the gate threshold and V _max is the maximum possible sperm velocity.

When tracking multiple trajectories of multiple spermatozoa, the method may use joint probabilistic data association filtering to determine trajectory paths. The joint probabilistic data association filter determines feasible joint association events between the detection object and the measurement object. The feasible joint association event ( A _js ) is the relative probability value between the detected sperm s and the measured sperm j . Next, the method makes a path assignment decision based on the best assignment method. A _js is defined as:

[z _j (k)]為該等偵測精子之高斯概率密度函數。 λ is a parameter,

[ z _j ( k )] is the Gaussian probability density function of the detected sperm.

Based on the series of frames over a time period, the method identifies a trajectory for each sperm, such as trajectory 1805 shown in FIG. 18 . The method then determines various parameters of sperm motility based on these trajectories. These parameters include, for example, curvilinear velocity (curvilinear velocity; VCL), straight-line velocity (straight-line velocity; VSL), linearity (linearity; LIN) and amplitude of lateral head displacement (ALH). Curve velocity (VCL) 1810 is defined as the sum of the movement distance per unit of time. Linear Velocity (VSL) 1815 is defined as the distance traveled in a straight line per unit of time. Linearity (LIN) is defined as VSL divided by VCL. The amplitude of lateral head displacement (ALH) 1820 is defined as twice the magnitude of the lateral displacement of the sperm head relative to the mean path 1825 .

In some embodiments, velocity curve (VCL) 1810 can be used to determine sperm motility. The method may set a speed threshold. Any precision motor with a VCL above or equal to the speed threshold Sons were identified as active sperm. The remaining spermatozoa with a VCL below the velocity threshold were identified as inmotile spermatozoa. The level of motility was the number of identified motile sperm divided by the total number of sperm identified from the image.

The method can further analyze sperm morphology. A camera of meter device 70 or smart communication device 60 ("the device") captures a magnified image of the sperm sample. The captured image is the original image for determining the morphology of the sperm.

The method is based on segmented detection of the shape of sperm candidates. The method uses the position of the heads of the sperm as an initial point. Using a shape-dependent segmentation algorithm, the method segments the image of the sperm into a head section, a neck section and a tail section. For example, the method can segment the sperm using methods such as active contour modeling.

Based on each section, the method calculates various section parameters such as length and width. A classifier (such as a support vector machine, neural network, convolutional neural network, or AdaBoost algorithm) can be trained using a training data set that includes labeled samples. After training, parameters of various parts of the sperm can be fed into the classifier to determine whether the sperm has the proper morphology. In some embodiments, classifiers can be used in other applications such as detecting properties of cells and microorganisms.

Additionally, it was found in some cases that several areas of the image could be mistaken for sperm trajectories due to unstable voltages, flickering light sources, or other types of noise. Figure 46 shows an example image including many misclassified regions. In Fig. 46, a small area 4601 is classified as a motion trajectory, which is actually static. To reduce external noise, the processor may employ analytical algorithms to determine sperm motility characteristics to minimize misclassification.

FIG. 47 is an example flow diagram of a process 4700 that may be implemented by the testing apparatus disclosed herein to accurately determine sample motion characteristics. Step 4710, for example: after inserting the carrier cartridge, the device can use the camera module to capture a plurality of images of the sample holding area of the carrier.

In step 4720, the device can adaptively select an analysis algorithm suitable for the movement characteristic of the biological sample to be tested based on the plurality of images. In some embodiments, the mobility characteristic indicates that the biological sample This essence is static or dynamic. After determining that the biological sample is substantially static, a static algorithm may be selected to process the captured image. In one example, the static algorithm can determine its morphology, such as the sperm acrosome and/or the middle segment of the sperm. In some embodiments, the static algorithm can also analyze sperm chromatin dispersion (SCD) staining images to determine the normality of sperm DNA fragments. On the other hand, after it is determined that the biological sample is substantially dynamic, dynamic calculation can be selected. In another example, dynamic algorithms can be used to determine the trajectory of hypermotile sperm. The dynamic algorithm helps to determine multiple parameters related to sperm motility, such as: VCL, VSL, VAP, ALH, etc. as shown in Figure 15, to optimize calculation efficiency.

In order to select an analysis algorithm in step 4720, according to some specific examples, the device may first select two images from the plurality of images. The device then compares the two images to determine the amount of change between the first and second images to determine which analysis algorithm is appropriate to use. The change amount can be determined according to the change rate of movement of the detectable target in the biological sample. For example, the detection device may compare the amount of change between the two images to a predefined threshold, indicating that the characteristic of the biological sample is substantially static or dynamic. If the variation is less than the threshold, the biological sample is considered static, and a static analysis algorithm is selected to process the captured image. On the other hand, if the change amount is greater than or equal to the threshold, the biological sample is determined as dynamic, and a dynamic analysis algorithm is selected for subsequent processing.

A plurality of images may include a series of images acquired over a short period of time. In some embodiments, 2 to 600 images can be acquired in 0.04 to 10 seconds (eg, at a rate of 60 images per second). In another specific example, the rate may be 15 images per second. For example, 45 images can be acquired in 3 seconds. The device may select two images that are each taken separately in time and/or sequence so that the amount of change between the two images is more pronounced. For example, the two images may be separated by 2 to 5 seconds (for example: select the first image and the last image in the sequence).

In step 4730, in this manner, the device can execute a set of analysis processing procedures corresponding to the selected analysis algorithm on the captured set of images to obtain analysis results related to the biological sample.

19 is a schematic diagram of a testing device including a collection bottle according to at least one embodiment of the present invention. The test strip device 1905 can be inserted into the test device 1900 through the insertion port. The test strip device 1905 may include a collection vial 1910 for collecting a sample (eg, a sperm sample) or include a well to receive a collection vial. The testing device 1900 may include a sensor (not shown) to detect whether the collection bottle 1910 is inserted into the testing device 1900 .

The testing device 1900 may have a timer mechanism for determining the period of time that the collection bottle 1910 has been inserted into the testing device 1900 . After inserting the collection bottle 1910 containing the sample, the test device 1900 may wait for a predetermined period of time (eg, 30 minutes) to liquefy the sample before prompting the user to transfer the sample from the collection bottle 1910 to the test strip device 1905 . In some embodiments, testing device 1900 may include a camera or sensor to determine whether a sample has liquefied.

Additionally, the testing device may include a movement mechanism to apply mechanical force to the collection bottle 1910 in order to mix the sample in the collection bottle 1910 . For example, the movement mechanism can shake, vibrate or rotate the collection bottle 1910, for example. In some other embodiments, the testing device can include a rod to be inserted into collection bottle 1910 and agitate the sample in collection bottle 1910 .

Testing device 1900 may optionally include a display (eg, screen 1920) for displaying information. For example, screen 1920 may show instructions or prompts on how to operate testing device 1900 . The screen 1920 can also show the test results after the test performed by the test device 1900 . Additionally or alternatively, the test device 1900 may include known communication modules so that it can communicate (e.g., analysis results and/or images captured by a camera module) with a user's computing device (e.g., a smartphone with a mobile software application, or a conventional personal computer such as a laptop). The test device 1900 is operable to receive instructions from a user (eg, from the screen 1920 and/or from the aforementioned communication module), and based on the instructions Execute a selected number of automated analytical processing procedures. The testing device 1900 can also display the results and/or an image of the sample on the screen 1920 or on the user's computer (eg, via the aforementioned communication module), or both.

Similar to the testing device shown in FIGS. 14A and 14B , testing device 1900 may include a camera (not shown) for capturing images or video of test strip device 1905 . The testing device 1900 may further include a processor (not shown) for processing images or videos for determining test results (eg, via the processing procedure shown in FIG. 16 ).

In some embodiments, for example, the magnifying component 2110 is a magnifying lens. The magnification capability of the magnification component 2110 can be represented by an angular magnification ratio or a linear magnification ratio. The angular magnification ratio is the ratio between the angular magnitude of the object as seen through the optical system and the angular magnitude of the object as seen directly at the closest photopic distance (ie, 250mm from the human eye). The linear magnification ratio is the ratio between the size of the image of the object to be projected on the image sensor and the size of the actual object.

For example, the magnifying lens may have a focal length of 6 mm, a thickness of 1 mm and a diameter of 2 mm. Assuming that 250mm is the near point distance of the human eye (that is, the shortest distance that the human eye can focus), the angle magnification ratio is 250mm/6mm=41.7 times. The distance between the magnification assembly 2110 and the sample holding area 2115 may be, for example, 9 mm. Therefore, the linear amplification ratio can be close to 2. In other words, the size of the image of the object on the image sensor caused by the magnification component is twice the size of the actual object below the magnification component.

In some embodiments, the magnifying element has a focal length of 0.1 mm to 8.5 mm. In some embodiments, the amplification component has a linear amplification ratio of at least one. In some embodiments, the linear amplification ratio of the amplification element is 0.5 to 10.0.

In some embodiments, a supplementary lens 2135 is placed under the camera module 2130 for further magnifying the image and reducing the distance between the magnifying component 2110 and the sample holding area 2115 . The effective linear magnification ratio of the entire optical system may be, for example, three. In other words, captured by the camera module 2130 The size of the image of the object is 3 times the size of the actual object in the sample holding area 2115. In some specific examples, the effective linear magnification ratio of the entire optical system of the test device is 1.0 to 100.0, preferably 1.0 to 48.0.

In some embodiments, the image sensor of the camera module has a pixel size of 1.4 μm. Typically, a captured image of an object needs to capture at least 1 pixel in order to properly analyze the shape of the object. Therefore, the size of the captured image of the object needs to be at least 1.4 μm. If the linear magnification ratio of the test device is 3, the test device can properly analyze the shape of an object having a size of at least 0.47 μm.

In some embodiments, the image sensor of the camera module has a pixel size of 1.67 μm. Then, the size of the captured image of the object needs to be at least 1.67 μm in order to properly analyze the shape of the object. If the linear magnification ratio of the test device is 3, the test device can properly analyze the shape of an object having a size of at least 0.56 μm.

In some embodiments, for example, the length of the entire optical system may be, for example, 24 mm. The distance between the bottom of the amplification component and the top of the sample holding area 2115 may be, for example, 1 mm. In some specific examples, the length of the entire optical system of the testing device is 2 mm to 100 mm, preferably 5 mm to 35 mm.

20 is a schematic diagram of a test device that does not include a collection bottle, according to at least one embodiment of the present invention. Unlike test device 1900, test device 2000 does not include a collection bottle or a slot for inserting a collection bottle. The sample is applied directly to the test strip device 2005 by the user or operator without being collected in a collection bottle.

FIG. 21A is a schematic cross-sectional view A-A of an embodiment of a testing device 1900 . The A-A section of the test device 1900 shows the camera module 2130 on top of the test strip device 2105 for capturing images or video of the sample holding area 2115 of the test strip device 2105 . The test strip device 2105 includes a magnification assembly 2110 on top of a sample holding area 2115 . Light source below test strip device 2105 2140 provides illumination to the sample holding area 2115. In some other embodiments, the light source may be placed on top of the test strip device or laterally to the side of the test strip device. There may be multiple light sources or an array of light sources for providing illumination on the test strip device. In some embodiments, different combinations of light sources may be switched, adjusted, or selected depending on the type of analyte so that the analyte is illuminated with light of the appropriate color.

In some embodiments, test strip device 2105 can include a test strip in or near sample holding area 2115 . For example, the test strips can be pH test strips, HCG (human chorionic gonadotropin) test strips, LH (luteinizing hormone) test strips or fructose test strips. When analytes of the sample in the sample holding area interact with chemical or biochemical reagents in the test strip, some optical properties of the test strip (eg, color or light intensity) can change. The camera module 2130 can capture the color or intensity of the test strip to determine the test result, such as pH level, HCG level, LH level or fructose level. In some embodiments, the magnifying assembly 2110 over the test strip can be replaced with a transparent or translucent cover. Thus, the test device can simultaneously check for an analyte in the sample and perform another analysis of the sample via one or more magnified images of the sample.

FIG. 21B is a schematic cross-sectional view of A-A of another embodiment of the testing device 1900 . The A-A section of the test device 1900 shows the camera module 2130 on top of the test strip device 2105 for capturing images or video of the sample holding area 2115 of the test strip device 2105, which includes a sensor and one or more lenses 2135 (also referred to as supplemental lenses or optical lens modules). A light source 2140 below (or otherwise disposed on) the test strip device 2105 provides illumination for the sample holding area 2115 . The magnification component 2110 can be attached to the bottom of the lens 2135 rather than on top of the sample holding area 2115 as shown in FIG. 21A. In some embodiments, the magnification component 2110 can be a flat light transmissive housing without magnification provided that the lens 2135 provides sufficient magnification. In some other embodiments, test device 1900 does not include magnification component 2110 if lens 2135 provides sufficient magnification capability (eg, if lens 2135 has a linear magnification ratio of at least 1.0).

22 is a schematic diagram of a test device of a test strip device with two sample holding areas. FIG. 29 shows an example of a carrier that may be suitable for a test device having a multi-camera configuration, such as the test device shown in FIG. 22 . Referring to FIGS. 19 and 20 concurrently, the test device shown in FIG. 22 may be another variation of test device 1900 (ie, with a collection bottle) or test device 2000 (ie, without a collection bottle). As shown in FIG. 22, a receiving mechanism is included in the test device to receive one or more carriers (e.g., a test strip device such as test strip device 2205, or a collection bottle such as bottle 1910) that are insertable through openings on the housing of the test device.

In some embodiments, a single carrier can include a first holding area and a second holding area, such as shown by test strip device 2205 in FIG. 22 . As shown in Figure 22, at least two camera modules may be included in the test device. The two camera modules include a first camera module 2230A and a second camera module 2230B configured to capture images and/or video of the first holding area 2215A and the second holding area 2215B, respectively. More specifically, the test strip device 2205 may include a first holding area 2215A and a second holding area 2215B. In some examples, a transparent or translucent cover 2210A is placed on top of the first retention region 2215A. The light source 2240A can be controllable and can provide illumination on the first holding area 2215A. The first camera module 2230A is positioned to capture images or video of the first holding area 2215A. As an optional implementation, the magnification component 2210B can be placed on top of the second holding area 2215B. Additionally, in some embodiments, the light source 2240B is operable to provide illumination on the second holding area 2215B. The second camera module 2230B is positioned to capture an image or video of the second holding area 2215B. The first holding area and the second holding area can directly carry biological samples or have been exposed to biological samples. Similar to the structure introduced with respect to FIG. 14B , in some embodiments, the testing device can include a collimator for collimating the light beam emitted by the light source to at least one of the holding regions. In some embodiments, an annular aperture can further be included between the light source and the collimator for forming a hollow cone of light that travels through the collimator and then reaches the sample holding region. In some additional embodiments, a phase plate may be included in the sample between the holding area and at least one of the camera modules for phase shifting the light reflected by the sample holding area.

As an alternative to a single carrier with multiple holding areas, multiple carriers can be inserted into the test device through their individual openings, ports or slots. For example, two independent test strip devices may respectively include a first holding area 2215A and a second holding area 2215B. Depending on the needs of the test, the positions of the first holding area 2215A and the second holding area 2215B in the test strip can be designed to align with the first camera module 2230A and the second camera module 2230B. In some embodiments, two test strip devices are inserted into the test device via two independent insertion ports.

Among other benefits, convenience and ease of testing are two significant benefits that the testing devices disclosed herein can provide. According to embodiments herein, a user of the disclosed test devices does not have to have any specialized knowledge about how to perform various types of analyzes on biological samples before the user can utilize the test device to produce results. Accordingly, a test device may include a processor for executing an automated analytical processing procedure on a sample and determining a result with respect to the sample. The processor may be carried by a main circuit board (ie, known components, not shown for simplicity). Additionally, the test device is preferably small and not as bulky as conventional test devices commonly found in laboratories. Thus, in some embodiments, such as those shown in Figures 19 and 20, the receiving mechanism of the carrier, the camera module and the main circuit board may all be enclosed within the housing of the test device. The test device may have a relatively small physical size, such as less than 30 centimeters (cm) x 30 cm x 30 cm, ie, 27,000 cm ³ . In some embodiments, the testing device can further include a battery compartment enclosed within the housing such that a battery can be mounted in the battery compartment to power the testing device.

In some embodiments, a processor included in the test device can perform different analyzes on different holding regions, and can derive results based on a combination of the results of the analyzes performed on the different regions. In other words, the processor may be configured to execute a first analysis processing program on the captured image of the first holding area, execute a second analysis processing program different from the first analysis processing program on the captured image of the second holding area, and determine the results of both the first analysis processing program and the second analysis processing program. result of the physical sample. As used herein, the term "analytic process" means a process that can evaluate one or more pieces of information collected from a number of sources (e.g., images of a held region) and produce results, conclusions, final results, estimates, or the like about the sources.

According to some examples, the testing device may use a combination of first camera module 2230A, light source 2240A, and housing 2210A to quantify an analyte or determine a characteristic of a sample (eg, pH level, LH level, HCG level, or fructose level). In addition, the test device can further use the combination of the second camera module 2230B, the light source 2240B and the magnifying component 2210B to analyze the magnified image of the sample to determine the characteristics of the sample (eg, sperm count, sperm motility, sperm morphology, etc.). Depending on the requirements of various types of biochemical tests, different combinations or configurations of light sources can be used to illuminate biochemical samples. Multi-camera configurations are particularly beneficial because different analysis processes can be performed via different camera modules without requiring the user to change carriers (eg, test strip devices), thereby speeding up result generation and reducing the complexity of necessary human operations. Light sources 2240A and 2240B are housed inside the housing and configured to illuminate the biological sample for at least one of the camera modules. According to one or more embodiments, the processor is configured to control the light source based on the analytical processing program that the processor is currently configured to execute.

In addition, in some embodiments, the processor may execute different analysis processing programs based on visual cues on the carrier. For example, some embodiments may perform image recognition and processing on the image of the holding region, and may perform different analytical processing procedures based on visual cues from the results of the image recognition. Example vectors 2905(1 ) to 2905(4) are shown in FIG. 29 , wherein vector 2905(1 ) is used for fertility tests on germ cells of male subjects (eg, via their sperm), and vectors 2905(2), 2905(3) and 2905(4) are used for fertility tests of germ cells of female subjects (eg, via their urine). As shown, carriers 2905(1 )- 2905(4) all have a first retention area 2915A corresponding to the location of the first camera module 2230A, but only carrier 2905(1) includes a second retention area 2915B. In some examples, the visual cue on the carrier may be the shape of a particular retention area (eg, first retention area 2215A). For the discussion herein, the shape of the holding area means the overall edge (or outer perimeter) of the holding area. side). For example, the shape may be circular, oval, triangular, rectangular, or any suitable shape recognizable by a processor utilizing known image processing techniques on an image of the holding area as captured by an individual camera module (eg, first camera module 2230A). Additional examples of visual cues may include graphic patterns, visual signs, one-dimensional bar codes, multi-dimensional pattern codes (eg, QR codes), and the like.

Referring to FIGS. 22 and 29 concurrently, in some embodiments, when the processor identifies (e.g., via the first camera module 2230A) that the first holding region (e.g., the first holding region 2215A of the carrier 2905(1) or the first holding region 2915A) has a first shape (e.g., a circle), the processor is configured to perform an analysis process (e.g., male subject's fertility, such as according to various characteristics of his sperm sample), When the first holding area 2215A or the first holding area 2915A) of ) is in the second shape (e.g., oval), the processor will perform a different analysis process (e.g., an analysis of a female subject's fertility, such as hormone levels based on her urine sample). In this way, the test device is not limited to performing only one type of test (eg, sperm fertility), but it can also switch the analysis process accordingly based on the carrier (eg, test strip device) inserted into the machine.

More specifically, according to some implementations, when the shape indicates that the biological sample includes sperm from a male subject, then the processing program may determine one or more properties of the sperm, such as those introduced herein. In some examples, the determination of one or more characteristics of the sperm may be performed by using the second camera module 2230B. For some specific examples, the determinable properties may include: sperm concentration, sperm motility, and/or sperm morphology. According to some embodiments, the processor is configured to (1) determine sperm concentration and/or sperm morphology based on a single of the captured images, and (2) determine sperm motility based on two or more of the captured images.

In view of the above, FIG. 30 is a flowchart of an example process 3000 for analyzing the fertility of both male and female subjects using the test devices disclosed herein (eg, in FIG. 22 ). With continued reference to FIG. 29, the processing routine 3000 is described below. It should be noted that the following example first implements A sample of males is added, followed by a sample of females, but the reverse order (ie, females followed by males) can be performed without affecting the precision of the results.

First in step 3002, a user may apply a biological sample (e.g., sperm) of a male subject to a first holding area (e.g., first holding area 2915A) and a second holding area (e.g., second holding area 2915B) of a first carrier (e.g., carrier 2905(1)). Next, in step 3004, the user inserts the first carrier into the testing device (e.g., the one shown in FIG. 22), and because the first holding region 2915A of the carrier 2905(1) is circular in shape, the testing device can automatically acquire the knowledge that the current sample contains sperm from a male and select the analysis processing program accordingly. Next, in step 3006, the user can use the test device to determine one or more characteristics of the sperm. For example, as discussed herein, a processor in the testing device may utilize the first camera module 2230A to acquire an image of the first retention region 2915A of the carrier 2095(1) (which may include test strips showing different colors in response to different acidities), and identify the color of the test strip to determine the acidity of the sperm. In addition, in step 3006, the processor in the test device may utilize the second camera module 2230B to determine one or more characteristics of the sperm selected from the group consisting of: cell count (e.g., sperm count), sperm concentration, sperm motility, and sperm morphology.

Next, in step 3008, the user may apply urine from the female subject to the first retention region 2915A of the second carrier (eg, carrier 2905(2)). In step 3010, the user inserts the second carrier into the testing device, and since the first holding area 2915A of the carrier 2905(2) is oval in shape, the testing device can automatically acquire the knowledge that the current sample contains urine from a woman and select the analysis process accordingly. In step 3012, the test device determines one or more characteristics of the urine, for example by utilizing the second camera module 2230B. For example, a test strip may be adapted to enable the test device to determine the concentration level of one or more types of female hormones (eg, FSH, LH, or HCG). Finally, in step 3014, the user utilizes the test device to automatically analyze the results of the male and female biological samples and determine the final results regarding the subject's fertility.

In some specific examples, the first camera module 2230A may have a lower camera resolution than the second camera module 2230B, and thus the two cameras are used by the processor to perform different analysis processes. In addition, the first camera module 2230A may have a lower magnification ratio than the second camera module 2230B. Some instances of the first camera module 2230A may not have a magnification function at all, while the second camera module 2230B may have a fixed magnification ratio. In addition or as an alternative to the second camera module 2230B, which itself has a higher magnification ratio, the magnification component 2210B of the second holding area 2215B is as shown in FIG. 22 . In some implementations, the magnification ratio of the camera module may be adjustable (eg, controlled by a processor). Some examples of test setups provide that the first camera module 2230A has a camera resolution of 2 megapixels or higher, and the second camera module 2230B has a camera resolution of 13 megapixels or higher. In some examples, the second camera module 2230B can include a linear magnification ratio of at least 4.8x or higher.

In some of these examples, the processor further determines at least one additional characteristic of the sperm by using the first camera module 2230A. This additional characteristic may include the acidity of the sperm. For example, the carrier may include a pH indicator in the first retention region 2215A that represents the acidity of the sperm using a color that the processor may recognize to identify the acidity. Similarly, some examples provide that the processor may determine a biochemical characteristic of the biological sample based on the color of a region in one or more images of the first or second holding region.

Continuing with the above test device example with a multi-camera configuration in FIG. 22 and the carrier example in FIG. 29, in some implementations, when the processor identifies a first holding region (e.g., first holding region 2215A or first holding region 2915A of carrier 2905(2)) having a second shape, such as an oval shape, that may indicate that the biological sample includes urine from a female subject, the processor is configured to determine one or more characteristics of the urine. Determinable characteristics may include: LH level, FSH level and/or HCG level. Like acidity, determination of one or more properties of urine can be performed by using the first camera module. Similarly, a carrier may include an LH in a first holding region (e.g., first holding region 2915A of an individual carrier) Indicator (eg, as shown in carrier 2905(3)), FSH indicator (eg, as shown in carrier 2905(2)), and/or HCG indicator (eg, as shown in carrier 2905(4)).

Additionally, in some embodiments, the processor may utilize at least one of the two camera modules (e.g., first camera module 2230A) or another sensor (e.g., light sensor 2690 introduced below with respect to FIG. 26 ) to determine the readiness or validity of the biological sample prior to executing the analytical processing procedure. In some implementations, the readiness or validity of the test sample can be determined based on identifying whether the first visual indicia is displayed in a particular area of the first holding area (eg, first holding area 2915A). An example of this first visual indicator could be a line displayed in a designated area on the test strip, such as a red line. The aforementioned red line can be used as a quality control means that can indicate that a test is valid or results are ready. In addition, the first holding area 2915A may include another area displaying a second visual indicia representing test results regarding characteristics of the biological sample. An example of this second visual indication could be a line displayed in another designated area on the test strip for readiness

In some embodiments, the testing device can perform an action in response to a determination that the biological sample is not ready. In some examples, the action performed by the processor includes implementing a timer having a duration determined by the analysis process to be executed. In some other examples, the testing device further includes a movement mechanism, and the processor in the testing device can utilize the movement mechanism to apply a mechanical force to the carrier to improve the readiness of the biological sample. More details of the actions and mechanisms that may be implemented in the test device are introduced below with respect to Figures 25 (Figures 25A and 25B) and Figure 26 (Figures 26A and 26B).

The positions of the magnifying components (eg, of a camera module or of a test strip) and the positions of the light sources can be adjusted or selected as required for various types of analyte analysis. In a variant, the camera modules may have adjustable magnification ratios. In at least some of these examples, the processor is further configured to adjust a magnification ratio of at least one of the two camera modules based on an analysis process that the processor is currently configured to execute. As introduced above, when the biological sample package When sperm are included, the test device can be configured with a suitable camera module (for example, the second camera module 2230B) to achieve different magnification ratios for determining the motility and shape of the sperm.

It should be noted that the optimal distance between the camera module and the magnification component may have a low margin of error. For example, even a small deviation of 0.01mm from the optimal distance can prevent the camera module from capturing a clear image of the sample holding area. To fine-tune the distance between the camera module and the magnification assembly, the test setup may include an autofocus (AF) function. The autofocus function is the function of automatically adjusting the optical system (eg, adjusting the distance between components of the optical system) so that the object being imaged (eg, semen) is within the focal plane of the optical system. At least one or more embodiments also provide a mechanical focus mechanism controllable by the processor to cause at least one of the two camera modules to focus on a respective holding area. The mechanical focus mechanism is discussed in more detail below with respect to FIGS. 23 and 24 . The mechanical focus mechanism may be controllable to adjust the position of the lens in at least one of the two camera modules (eg, as generally shown in FIG. 23 ). Additionally or alternatively, the mechanical focus mechanism may be controllable to adjust the position of the carrier (eg, as generally shown in Figure 24).

FIG. 23 is a schematic diagram of components of a test setup with autofocus functionality. As shown in FIG. 23, the test apparatus can move the camera module up or down along the Z-axis (eg, by motorized rails, ultrasonic motor drive, or stepper motors). By adjusting the vertical position of the camera module, the test device can adjust the distance between the camera module and the amplifying component.

Fig. 24 is a schematic diagram of components of another testing device with autofocus function. As shown in Figure 24, the test device can move the test strip device up or down along the Z axis. By adjusting the vertical position of the test strip device, the test device can adjust the distance between the camera module and the amplifying component.

During the autofocus operation as shown in Fig. 23 or Fig. 24, the camera module and supplementary lens remain as a single module. In other words, the distance between the camera module and the supplementary lens remains constant during the autofocus operation as shown in FIG. 23 or FIG. 24 .

Fig. 25 is a schematic diagram of a test setup including a switch and a motor. The B-B cross-section of test device 1900 in Figure 25 shows various components of the test device. The testing device 1900 includes a switch 2550 for detecting the collection bottle 2510 inserted into the testing device 1900 . When collection vial 2510 is inserted, switch 2550 is activated. The collection bottle 2510 is then notified to the testing device 1900 via the switch 2550 . Based on the period of time switch 2550 is activated, the test device may determine the period of time collection bottle 2510 remains inserted.

The testing device 1900 further includes a motor 2560 for shaking, vibrating or rotating the collection bottle 2510 to mix the sample in the collection bottle 2510 . The testing device 1900 may include a camera 2570 to determine based on captured images of the sample in the collection bottle 2510 whether the sample has liquefied.

Figure 26 is a schematic diagram of a testing device including a flexible element. The B-B cross-section of the testing device 1900 in Figure 26 shows various components of the testing device. The testing device 1900 includes a moving element 2680 (eg, a resilient member) at the bottom of a slot for receiving the collection vial 2610 in a moving manner. For example, moving element 2680 may include a spring that spontaneously returns to its normal shape after contraction or deformation. When the collection vial 2610 is inserted into the slot, the moving element 2680 is compressed. The light sensor 2690 (or other type of distance sensor) is responsible for detecting the distance between the light sensor 2690 and the bottom of the collection bottle 2610 . Based on the distance between the light sensor 2690 and the bottom of the collection bottle 2610 , the test device 1900 can determine the weight or volume of the sample contained in the collection bottle 2610 . For example, the distance between the light sensor 2690 and the bottom of the collection bottle 2610 can be inversely proportional to the weight or volume of the sample contained in the collection bottle 2610 .

In some other embodiments, testing device 1900 may include a sensor on top of collection vial 2610 . The sensor may be responsible for detecting the distance between the sensor and the top of the collection bottle 2610. The weight or volume of the sample contained in the collection bottle 2610 may be determined based on the distance, since the volume or the weight may, for example, be proportional to the distance between the sensor and the top of the collection bottle 2610 . Then, based on the weight or volume of the sample, the testing device 1900 can determine a time period to wait for the sample in the collection bottle 2610 to liquefy. The testing device 1900 further includes a motor 2660 for shaking, vibrating or rotating the collection bottle 2610 to mix the sample in the collection bottle 2610 .

In some embodiments, the camera module of the test device may include a light field camera (not shown) for capturing the intensity and direction of light. A light field camera may include a microlens array or a multi-camera array in front of the image sensor to detect direction information. Using the directional information of the light, the camera module can capture sharp images at a wide range of focal planes. Therefore, a test device using a light field camera may not need an auto-focus function to finely adjust the distance between the camera module and the magnifying component.

In view of the above, the device of the present invention is suitable for testing male fertility and/or female fertility.

The present invention provides a method of testing male fertility using the device of the present application. The method comprises the steps of: applying a biological sample from a male subject to the first and second holding regions of the carrier; inserting the carrier into the device; determining the acidity of the sperm according to a first analysis procedure; determining one or more characteristics of the sperm selected from the group consisting of sperm concentration, sperm motility, and sperm morphology according to a second analysis procedure; and analyzing the results to determine male fertility.

The present invention also provides a method for testing female reproductive hormones using the device of the present application. The method comprises the steps of: applying a biological sample from a female subject to a first retention region of a carrier; inserting the carrier into the device; and determining a concentration level of one or more types of female hormones, such as luteinizing hormone (LH), follicle stimulating hormone (FSH), or human chorionic gonadotropin (HCG).

The invention further provides a method for testing the fertility of a pair of male and female subjects. The method comprises the steps of: applying a biological sample from a male subject to a first holding area and a second holding area of a first carrier; inserting the first carrier into the device; determining the acidity of the sperm according to a first analytical processing procedure; determining one or more characteristics of sperm selected from the group consisting of sperm concentration, sperm motility, and sperm morphology according to a second analytical processing procedure; applying a biological sample from a female subject to the holding region of the second carrier; device; determining the concentration level of one or more types of estrogen; and analyzing the results of male and female biological samples.

27 is a flowchart of a process for analyzing a semen sample from a male client or patient. A system for analyzing a semen sample may include a testing machine (eg, testing device 1900 ), a mobile device, and a cloud server. Figure 28 is a flowchart of a process for analyzing LH or HCG of a female client or patient. A system for analyzing LH or HCG may include a testing machine (eg, testing device 1900 ), a mobile device, and a cloud server. The flowcharts of FIGS. 27 and 28 illustrate the steps performed by the tester, the mobile device and the cloud server and the information transferred between the tester, the mobile device and the cloud server.

In some embodiments, a method for testing sperm comprises the steps of: obtaining an automated testing device for testing a biological sample for multiple view analysis, applying a sperm sample to a sample holding area, recording a video or image of the sperm sample; determining a sperm count of the sperm sample based on at least one frame of the recorded video or a recorded image; and determining sperm motility of the sperm sample based on the recorded video or recorded image.

In a related embodiment, the method further includes waiting a predetermined period of time for liquefaction of the sperm sample before applying the sperm sample to the sample holding region.

In another related embodiment, the method further includes: positioning a mobile device including a camera assembly on top of the device such that the camera assembly is aligned with the amplification assembly and the sample holding area; and receiving, by the mobile device, an amplified light signal from the sperm sample in the sample holding area via the amplification assembly.

In yet another related embodiment, the method further includes illuminating the sample holding area by a side illuminator disposed on a side of a carrier of the device or a vertical illuminator disposed on top or below the carrier of the device.

In yet another related embodiment, the method further includes: directing a light beam from the side illuminator through a carrier made of a transparent or translucent material; and reflecting the light beam to the sample holding area by a plurality of light reflecting patterns included in the carrier.

In yet another related embodiment, the method further includes inserting the disposable testing device into the base including a camera assembly for recording video of the sperm sample or a form-fitting frame for securing a mobile device including the camera assembly for recording video of the sperm sample.

In yet another related embodiment, the method further comprises: extracting at least one frame from the recorded video of the biological sample; identifying a plurality of sperm from the at least one frame; and calculating a sperm count based on the number of identified sperm and the area recorded by the at least one frame.

In yet another related embodiment, the method further comprises: analyzing a shape of the identified sperm; and determining a morphology level based on the shape of the identified sperm.

In yet another related embodiment, the method further comprises: extracting a series of video frames from the recorded video of the sperm sample; identifying a plurality of sperm from the series of video frames; identifying movement trajectories of the sperm based on the series of video frames; determining movement speed of the sperm based on the movement trajectory of the sperm and a time period captured by the series of video frames; and calculating sperm motility based on the movement speed of the sperm.

In yet another related embodiment, the method further comprises: further magnifying the video or image of the sperm sample via a magnifying lens.

In some embodiments, a method for testing sperm using a system for testing a biological sample, comprising: inserting a device into a base assembly; recording video of a sperm sample in a sample holding region by a mobile device, the mobile device secured in a form-fitting frame of the base assembly; determining a sperm count of the sperm sample based on at least one frame of the recorded video; and determining sperm motility of the sperm sample based on the recorded video.

In a related embodiment, the method further includes: further magnifying the video of the sperm sample through a magnifying lens.

In some embodiments, a system for testing a biological sample includes a disposable device and a base assembly for testing the biological sample. The disposable device includes a sample carrier including a sample holding area and a removable cover placed on top of the sample holding area. The base assembly includes an insertion port for inserting the disposable device into the base assembly, and a camera assembly for capturing images of the sample holding area, the camera assembly including an image sensor and an optical lens module. In a related embodiment, the optical lens module can have a linear magnification ratio of at least 0.1.

FIG. 31 illustrates an additional example carrier 3105 with one or more visual indicators 3117(1)-3117(5) (or may be collectively referred to as visual cues 3117) that may be used to control the analysis processing performed by a test device (e.g., the test device shown in FIG. 21C or FIG. 22). As shown in FIG. 31 , visual cue 3117 may be in (or near, in some additional or alternative embodiments) a holding area of carrier 3105 (eg, holding area 3115B).

As previously described (eg, with respect to Figure 29), the processor may execute different analysis processes based on visual cues on a carrier. For example, in some specific embodiments image recognition may be performed and the image of the holding area may be processed and different analysis processes may be performed based on visual cues from the image recognition results. In some embodiments, the visual cue of the carrier may be a shape of a particular holding area. Additional examples of visual cues may include graphic patterns, visual signs, one-dimensional barcodes, multi-dimensional patterned codes (eg, QR codes), and the like.

In some specific examples, as shown in FIG. 31 , any visual indicia (eg, visual indicia 3117(1)) can be a specific small graphic pattern that can be imprinted, attached, or marked on holding area 3115B in carrier 3105. In the example of FIG. 31 , visual indicia 3117(1)-3117(5) are all the same or substantially similar patterns, however in other examples (not shown for simplicity), they need not be identical and each visual indicium may have a unique shape, size, pattern, etc. implemented in one or more Here, a visual cue 3117 (e.g., visual markers 3117(1)-3117(5)) is a size that is not perceived by humans but can be recognized by a camera module (e.g., second camera module 2230B in FIG. 22 or camera module 2130 in FIG. 21C) after magnification through a microlens. In some of these implementations, the visual markers 3117(1)-3117(5) are smaller than 15 micrometers (μm), and furthermore, the visual markers 3117(1)-3117(5) can be configured such that their positions collectively form a pattern (e.g., a predetermined configuration). Additionally or as an alternative to characteristics specific to the visual markers (e.g. size, shape, color and/or position), the collective pattern formed by the position of each visual marker may be a recognizable cue to be used to control the functionality of the test device (e.g., whether and subsequently which analytical procedures are performed). This collective pattern can be based on the absolute position of the visual markers (eg, at the holding area) and/or the relative position of the visual markers (eg, from their respective neighboring markers). In FIG. 31 , the collective pattern shown by visual markers 3117(1)-3117(5) is that visual markers 3117(1)-3117(4) are each placed in one of the four corners (camera-captured image) and visual marker 3117(5) is placed in the center, and each visual marker is evenly distributed. Some additional or alternative embodiments provide that each (or each group) of specific visual indicia (or signs) on the visual cue may represent a different analysis function to be performed.

In view of the above, the test device herein can utilize visual cues on the carrier (eg, in or near the holding area) to control the functions of the test device and adaptively execute analysis processing procedures based on the visual cues. In some embodiments, a visual cue may be used to confirm whether the carrier is an authorized carrier (eg, properly licensed and manufactured under certain specifications and according to applicable quality standards). In other examples, visual cues can be used to control in which mode the test device performs calculations (eg, male or female, laboratory or home, high accuracy or short time, on battery or plugged in). Additionally, providing visual cues in some embodiments may be used to control access to certain functions of the test device, which provides the ability to flexibly customize the services provided by the test device based on customer identity, geographic location, and the like.

FIG. 32 is a flow diagram of another example of a process 3200 that may be implemented by a test device disclosed herein (as in FIG. 21C or 22 ) adaptively executing an analysis process based on visual cues. With continued reference to FIG. 31 , processing routine 3200 is described below. It should be noted that in the following instance of handler 3200, the visual Hints are applied to execute a bearer authentication application, however the process can be equally adapted to execute other applications (eg, as described with respect to FIG. 30). For example, in some applications other than carrier authentication, the processor may execute different sets of analytical processing procedures based on different visual cues.

First, in step 3202, the receiving mechanism of the test device receives the carrier inserted through the opening, the sensor (not shown for simplicity) can notify the processor, and the processor will cause the built-in camera module of the test device to capture images of one or more carrier holding areas. At step 3204, the processor may utilize the captured image to identify visual cues in the carrier (eg, based on known image analysis techniques or those disclosed herein). As discussed above, the visual cues may include a number of visual cues, each of which may be the same or different size, shape, pattern, color, etc. (as shown for example in FIG. 31 ) or they may be different. The visual signs can collectively further present a pattern (eg, from their location). The processor can then compare the visual cues (e.g., characteristic size, shape, location, or set pattern) with predetermined visual cues (e.g., stored in local memory and/or cloud databases (operable or controllable by the manufacturer or other administrator of the test device).

In step 3206, the processor selectively executes a set of analysis processing procedures on the captured image of the holding area based on the recognition result of the visual cue. If the recognition result of the visual cue is positive (e.g., responding to a carrier holding area with a predetermined visual cue), then the processor proceeds with subsequent steps which may include optionally capturing additional images (or video) for analysis (step 3208) and performing a corresponding set of analysis processing procedures on the images (step 3210). On the other hand, if the recognition result returns negative (e.g., responding to a carrier holding area that does not have the predetermined visual cue), the processor causes an alternative action (e.g., displays an error code) reflecting the unrecognizability of the visual cue, and does not perform any analysis processing on the image (step 3212). After the set of analysis processing procedures is executed, the processor can continue to determine the results about the biological sample based on the results of the analysis processing procedures as described above.

In addition, it is worth noting that traditional computer-assisted sperm analyzers (CASA) rely on large-scale microscopes and the experience of operating technicians to determine the parameters of sperm. number. There are several computer software aids to supplement the technician's experience and to standardize the analytical results. However, due to differences in lenses and sensing modules, blurred images often seriously affect the effectiveness of assistive software, resulting in inaccurate related functions (such as sperm count calculation).

In addition, competent authorities such as the World Health Organization (WHO) publish human semen examination and processing laboratory manuals, which specify the minimum sample size (for example, 200 spermatozoa) to be evaluated to determine sperm concentration, sperm motility, and sperm morphology. Existing computer-assisted sperm analysis image-based analysis generally lacks automatic sampling or requires manual operations to obtain multiple fields of view to meet the World Health Organization specification and reduce sampling errors in the analysis. Instead, if sampling is performed repeatedly with only a single field of view, the time it takes to repeat the procedure often becomes too long to be realized on a large scale in order to achieve a satisfactorily low sampling error.

FIG. 33 is an example flow diagram of a process 3300 that may be implemented by a test device herein (eg, FIG. 21C or FIG. 22 ) for a better outcome (eg, better assay accuracy or efficiency). Handler 3300 may be an alternative or supplemental handler to the handlers herein (eg, the handler shown in FIG. 16 ).

First, step 3310 (e.g., after insertion of the carrier cartridge carrying or exposed to the biological sample (as introduced above)), the introduced device may utilize a camera module to capture one or more images (or collectively, imagery) of the carrier cartridge holding area. In some optional embodiments (eg, as described with respect to FIG. 29 or 31 ), the device may recognize (step 3320 ) a visual cue on the carrier from the captured set of images of the holding area. In these alternative embodiments, the device may perform a set of analytical processes on the captured set of images based on the recognition of the visual cues.

In step 3330, the device may divide the captured set image into a plurality of blocks. In some embodiments, tiles may be polygonal. More specifically, some implementations state that tiles may be triangles, rectangles, squares, pentagons, hexagons, and the like. These (blocks') shapes may have at least one side usually 0.05 mm. In one or more embodiments, the blocks are square and have dimensions 0.05 mm by 0.05 mm. It is worth noting that, depending on the specific implementation, the number and size of the blocks can be adjusted according to the resolution of the camera module. An example segmentation of an image indicating a holding region into blocks (eg, block 3402 ) is illustrated in FIG. 34 . It should be noted that for purposes of facilitating the discussion of the disclosed techniques herein, the captured aggregate image is considered to be "segmented" into blocks; however, it should be appreciated that in one or more implementations, the processor need not actually perform mathematical division operations to perform this technique at computer runtime (or during normal operation); rather, the resulting blocks or grids may be predetermined, logically prewired, pre-programmed, or pre-configured on the camera controller and/or processor of the device so that the need to perform computations associated with the aggregate image being segmented into blocks may be reduced, or in some instances is completely eliminated.

In step 3340, the example device selects from the plurality of blocks, candidate blocks, for analysis. According to one or more embodiments, the selection of candidate blocks is based on many factors, such as the degree of focus of a certain block and/or the normality of a certain block.

More specifically, in many implementations, the apparatus may determine (step 3342) the degree of focus for each of the plurality of blocks, such that each block can have a corresponding measure of focus. The degree of focus can be determined based on one or more focus measurement functions. Depending on the implementation, the adopted focal length measurement functions may include one or more of: variation, sum of variance coefficients, Laplace energy image, and/or lateral gradient strength maximization.

After determining the focus level of each block, in some embodiments, the apparatus compares the focus level of a block with a minimum focus level threshold. In one or more implementations, a block may be selected as a candidate block only if the focus level satisfies (eg, meets or exceeds) a minimum focus level threshold. In addition, the device can also mark or label blocks. This means, in one or more embodiments, that blocks are marked or labeled (eg, for further analysis or tracking identification) only if they meet a minimum focus threshold. Marking or numbering can be done sequentially or randomly. In Figure 35 it says This is part of the selection process of candidate blocks, where the blocks are randomly marked, and the blocks exceeding the minimum focus degree threshold are preliminarily selected as candidate blocks 3510 .

Next, the device can perform an image processing program on several selected blocks to determine the characteristics of the selected blocks (step 3344), to determine the normality of a block, for example, to check whether the block is "normal enough" to grant further analysis. In some examples, the blocks selected for normality determination are those that have been preliminarily selected as candidate blocks (eg, those satisfying a minimum focus threshold, as described above). In some instances, the characteristic used at this stage to determine normality is cell count (eg, sperm count). In a specific example, the device may perform an image processing procedure on the blocks satisfying the minimum degree of focus (ie, they are sufficiently focused) to determine the number of cells (sperm) in the block for each sufficiently focused block. The image processing procedure may include binarization (and in some implementations, with adaptive limitation) to identify a part of the object that may be sperm in the block as the foreground, and identify the rest of the block as the background. After the image processing process, the device can determine the number of cells (sperm). In one or more embodiments, the cell count of a candidate block may be determined based on the ratio of areas with and without sperm (eg, by extrapolation using a table with known cell ratios).

The apparatus is then able to calculate statistics (eg mean and standard deviation) of all remaining candidate blocks (eg those satisfying a minimum focus threshold). After the statistics are calculated, the apparatus can determine (step 3344 ) the normality of a particular block by statistically comparing one or more characteristics (eg, sperm count) of the particular block with all remaining candidate blocks. In some embodiments, only if the normality of a specific block satisfies a normality condition, it will be continuously selected as a candidate block. Taking sperm count as an example, in various embodiments, a block is considered "sufficiently normal" (eg, satisfies the condition of normality) when the sperm count in the block is within a predetermined value of standard deviation from the mean of the plurality of blocks. In one or more implementations, the requirement for normality is to be within two standard deviations (of the mean). In other implementations, the normality requirement is one or three standard deviations, or other suitable statistical technique, that reflects the normality of a block compared to other groups of blocks. illustrated in Figure 36, this figure is shown in Figure Like results after processing procedures (eg adaptive thresholding binarization) and cell number determination. It should be noted that in FIG. 36, the estimated cell number of each candidate block is shown instead of its label.

Additionally, the device can determine (step 3346) whether the target number of cells to be analyzed has been reached. In particular, one or more embodiments of the disclosed apparatus are capable of maintaining a total cell count, and for each block selected as a candidate block, the device adds the corresponding cell count for that block to the total cell count. The device can control the number of biological samples to be analyzed with the target number of analyzed cells, and the number is configurable according to the implementation. This quantity (number) can be customized according to laboratory manuals and standards for testing specific biological samples. In some embodiments, the target number of cells to be analyzed is two hundred (200). In some instances, when the total cell volume reaches the target number of cells to be analyzed, the selection of candidate blocks is completed. That is, according to at least some of the embodiments disclosed herein, selection of candidate blocks can be performed (eg, in a random manner) on blocks that meet the focus threshold and the normality of the total cell count to a target number of cells to be analyzed.

At step 3350, after selecting candidate blocks, the introduced device can determine one or more characteristics of the biological sample by analyzing the selected candidate blocks (eg, by one or more techniques described herein). In at least several embodiments, the biological sample is semen, and one or more characteristics of the biological sample are to be determined in the candidate block, including one or more of: cell number (or concentration, which can be inferred from cell number), motility, or morphology. In some examples, the device is further configured, after execution of the set of analytical processing procedures, to determine a result (eg, fertility) regarding the biological sample based on the results of the analytical processing procedures.

Furthermore, it has been observed here that it is often difficult (especially in large quantities and cost-controlled) to perfectly manufacture optical lens assemblies such as microscopic lens assemblies and/or magnifying lens assemblies mounted on the test apparatus introduced here. Lens defects exist in various forms, such as impurities, or imperfections in the lens itself (eg, sharpness, refraction, focus, etc.), and these Imperfections can adversely affect the accuracy of the test device. Introduced here, therefore, are calibration and qualification techniques to mitigate lens imperfections and further improve the analytical accuracy of the test apparatus disclosed herein.

FIG. 37 is an example flow diagram 3700 of a calibration process that may be implemented by a testing device disclosed herein (eg, FIG. 21C or FIG. 22 ) to obtain improved results. This process 3700 may be an alternative or supplemental process to the processes disclosed herein, such as the process illustrated in FIG. 16 .

First, in step 3710 (eg, after the carrier case is inserted), the incoming device can utilize the camera module to capture one or more images (or collectively, imagery) of the carrier case holding area. In some optional embodiments (e.g., those described with respect to FIG. 29 or 31 ), the device may identify (step 3720) a visual cue on the carrier from the captured collective image of the holding area. In these optional embodiments, the device may perform a set of analysis processes on the captured collective image based on the results of the recognition of the visual cue described above.

More specifically, in some implementations, the carrier box herein can serve as a dedicated virtual box that can be used to trigger the calibration process. For example, a dedicated dummy box may carry one or more dedicated graphic patterns (eg, described below with respect to FIG. 38 ) that, after a visual cue recognizes the handler (eg, in step 3720 ), can trigger the test device to enter calibration mode. In another example, a dedicated virtual box can carry a dedicated test sample (eg, as described below with respect to FIG. 41 ), and the user can manually cause (eg, through an on-panel user interface or a remote tester) the test device to enter calibration mode. In many instances, the virtual box may include an electronic (eg, a radio frequency identification (RFID)) or a mechanical feature (eg, a special shape or mechanical protrusion) that triggers the correction mode.

Figure 38 is a test carrier carrying a visual cue or an image pattern that can be used to calibrate or verify the test devices disclosed herein. In one or more embodiments, the visual cue includes a An image pattern that the test device can recognize as a trigger to enter calibration mode. Afterwards, the test device can capture an image of the image pattern using the camera module, and perform self-diagnosis to correct itself from the results in the captured image. Visual patterns should be easily identifiable (and not easily mistaken). As illustrated in FIG. 38 , visual patterns in examples include repeating (eg, every 0.08 millimeters, ie, repetition rate or "pitch"), larger (eg, 0.02 millimeters by 0.02 millimeters), and generally regular shapes. This visual cue can go a step further by including one or more repeating linear styles. In the example illustrated in FIG. 38, this linear style includes a set (eg, three) of horizontal lines and a set (eg, three) of vertical lines. In some embodiments, the lines have a resolution of 200 line pairs per millimeter (LP/mm) or higher. In the particular example of Figure 38, the lines have a resolution of 500 LP/mm. It should be noted that horizontal and/or vertical lines are examples of visual linear patterns suitable for assisting the test device in performing self-diagnosis of the optical properties and performance of optical instruments (e.g., microlenses) specific to the test device itself; other suitable visual patterns may be substituted for the illustrated example in FIG. 38. For example, in some embodiments, an "E" shaped pattern or equivalent may be used as a visually linear pattern instead of parallel lines. For example, in some implementations, solid and dashed lines can be used for visual linear patterns.

Continuing with process 3700, although the correction mode has been initiated at step 3730, after the aggregated image of the carrier is captured (eg, at step 3710), the device can segment the captured aggregated image into a plurality of blocks (this is similar to step 3330, discussed above). In some embodiments, tiles may be polygonal. More specifically, some implementations indicate that the blocks can be triangular, rectangular, square, pentagonal, hexagonal, etc. These shapes (of blocks) may have at least one side of 0.05mm. In one or more embodiments, the blocks are square and measure 0.05 mm by 0.05 mm. It is worth noting that, depending on the particular implementation, the number and size of blocks can be adjusted according to the resolution of the camera module. In one or more implementations, the above-mentioned spacing (eg, the rate at which the visual pattern regularly repeats itself) can correspond to the number of blocks into which the collective image can be divided. In some embodiments, the spacing may correspond to the number of tiles in which the collective image can be divided by the test device.

In step 3740, the device of the example can perform a calibration/self-diagnostic procedure, eg, on each block. The calibration procedure should generally be one or more steps, enabling the test device to autonomously self-diagnose the quality of the optical modules (eg, including microlenses, camera modules) currently installed on the test device itself. In one or more embodiments, the test device may determine (at step 3742) the degree of focus of each block, eg, by using one or more focus measurement functions. Examples of focal length measurement functions may include variant, sum of coefficient of difference, Laplace energy image, and/or lateral gradient strength maximization types. Next, at step 3744, the tester can determine whether a region satisfies a degree of focus, eg, the minimum degree of focus threshold discussed above. Additionally or alternatively, the test device can compare (at step 3746) the retrieved results to one or more expected results. For example, the tester's processor accesses one or more images pre-installed in memory (e.g., not captured using a camera, e.g., passed on or installed by default), compares them with the captured images, and determines whether the quality of the captured images in question in the block meets minimum standards. The preinstalled image or images shall be representative of the visual pattern applied to the correction. In step 3746, the testing device can compare and review sample image quality parameters, including color distortion, pattern distortion, sharpness artifacts, and/or other image artifacts.

Fig. 39 is an example image of a visual cue to Fig. 38, captured by the test device disclosed herein, the image quality is generally better toward the lower left corner and worse toward the upper right corner. 40A and 40B are two specific examples illustrating different image qualities of the captured images in different blocks in FIG. 39 . In some embodiments, images 40A and 40B can each represent one block, for example, where the pitch corresponds to the number of blocks by which the collective image can be divided. As illustrated, the image quality in the block of FIG. 40A is better than that of FIG. 40B because the image is clearer and more focused.

Returning to process 3700, in step 3750, the result of step 3740 (e.g., whether the block meets minimum image quality requirements, such as minimum focus) is recorded in a computer-readable storage medium (e.g., may be non-transitory, such as flash memory) incorporated in the test device (not to be described here). Knowledge gained from correction handlers can, for example In other words, when the test device is then utilized in normal operation. In one or more embodiments, during normal operation (eg, in step 3340, discussed above) at this point the test device may automatically skip or ignore those blocks that do not meet the minimum image quality requirements during calibration or self-diagnosis. As such, the testing apparatus disclosed herein can mitigate adverse effects of lens imperfections and increase analytical accuracy.

Figure 41 discloses an example image of a test carrier carrying a test sample, which can be used to calibrate or verify the test device disclosed herein. This technique can be applied to one or more of the aforementioned embodiments, where a dedicated dummy box can carry a specific test sample and the calibration mode can be activated by a trigger other than a visual pattern (e.g. manual activation by the user, or by a mechanical feature or radio frequency identification (RFID) on the dummy box). Certain embodiments indicate that the test sample should be in the form of an aqueous medium (eg, a liquid solution) containing small test particles, such as test particle 4102 illustrated in FIG. 41 . These microparticles can be made of any suitable substance including, for example, polymers. A particular example substance for particles 4102 is latex. The size of the particles can be tailored to a particular application. In some implementations, the size of the particles can be similar to those of cells, such as sperm. Example sizes of particles may range from 0.5 microns to 50 microns in diameter. In the example, the particles are 5 microns in diameter. When the test particle is used as a sample, the test device can perform calibration/self-diagnosis without step 3720 as the processing procedure 3700, and self-diagnose the quality of the optical module currently installed in itself. In some of these implementations, the test device may preload images of the test particles (eg, not captured by a camera, eg, by being transmitted or otherwise programmed) in memory, such as discussed above, for comparison and calibration purposes.

42A and 42B illustrate different image qualities in different blocks of the captured image in FIG. 41 . As explained, the image quality in the block in Fig. 42A is better than that in Fig. 42B because the image is clearer and more focused. Similar to the discussion above, with respect to step 3750, the knowledge of the baseline image quality of each block can be used, for example, to be exploited later in normal operation of the test device. For example, some test device embodiments may automatically skip or ignore those blocks or self-diagnostics. As such, the test apparatus disclosed herein can mitigate adverse effects of lens imperfections and improve analytical accuracy.

In some embodiments visual cues (eg, discussed in relation to FIG. 31 ) can help the test device determine the status of the carrier or sample holding area (eg, the area is dry or wet, or is carrying a good sample). FIG. 43 is an example flowchart of a process 4300 that may be implemented by a test device disclosed herein (eg, in FIG. 21B or 22 ) to verify that a sample holding region carries a biological sample.

In step 4310 (eg, after a carrier cartridge is inserted), the device may utilize a camera module to acquire one or more images (or aggregated images) of the holding area of the carrier cartridge. Step 4320 The device may identify visual cues on the carrier based on the captured set of images of the holding area. Visual identification includes step 4342 verifying whether the holding area carries a biological sample based on the visual cues shown in the captured set of images. The identifying further includes, at step 4344, selectively causing the processor to execute the set of analysis processing procedures on the captured set of images according to the verification results. In step 4330, the device may execute the set of analysis processing procedures on the captured set of images according to the recognition results of the visual cues.

44A-B show examples of captured collective images of an empty or dry sample holding area. 45A-B show examples of captured images of a sample holding region loaded with biological sample-carrying fluid. In these particular examples, each captured image shows a visual signature of a micrographic pattern. The shadow of the visual mark is clearly visible on the empty or dry sample holding area. The fluid carrying the biological sample will cause the sample holding area to exhibit a different refractive index compared to an empty carrier cartridge, thus affecting the captured shape of the visual signature. Shadows of visual markers fade due to refraction. For example, the captured shape of a visual signature with a biological sample will be optically distorted compared to the template (eg, the captured shape of a visual signature without any sample as shown in FIGS. 44A-B ). Therefore, by comparing the captured shape of the visual mark with the template and evaluating the degree of distortion, such as determining the border thickness of the mark or the shadow area, etc., the processor can determine whether the holding area is really loaded with the biological sample to be tested. Here, the distortion threshold represents the degree of optical distortion that indicates the presence of the biological sample in the holding area. special Yes, the degree of distortion can be compared with a preset threshold to verify whether the carrier carries a biological sample. In many implementations, different thresholds can be defined based on the algorithms and/or heuristics employed, for example, algorithms such as pixel gradient direction and intensity detection can be used to determine the corresponding thresholds.

In some embodiments, the template can be generated by capturing an image of an empty carrier cassette during the configuration phase and storing image data representing visual cues of the captured image prior to testing any biological samples. In some embodiments, templates may be stored on the device to reduce the number of operations that need to be performed during the configuration phase. In some embodiments, the visual cues can be compared to stored images to determine their dissimilarity. When the difference is lower than a preset threshold, the processor may determine that the holding area carries a biological sample.

If the processor verifies that the sample holding area carries a valid sample, the processor proceeds to analyze the captured image. However, if the processor cannot verify based on the comparison that the sample holding area carries any valid (e.g., when the analysis task to be performed (in some instances identifying the shape of the holding area as described above) requires a fluid sample, rather than a fluid) biological sample, then the processor does not perform any image analysis. Instead, in some embodiments, the device notifies the user that an invalid sample was provided. The notification may be shown with a signal or indicia indicating that no biological sample has been provided.

In some cases, as previously mentioned, CASA-based image analysis often lacks automatic sampling or requires manual image post-processing to obtain multiple fields of view to meet WHO specifications. To address this issue, the test apparatus may include a positioning mechanism operable to adjust, with or without human intervention, the relative position of the carrier to the camera so that images may be acquired with a plurality of adjacent fields of view.

FIG. 48 is an example flow diagram of a process 4800 that may be implemented by a test device disclosed herein to utilize multiple fields of view to improve results. Step 4810, for example, after the carrier cartridge is inserted, the device may utilize a camera module to capture a first image of the sample holding area of the carrier. Step 4820 device identifies the first image In step 4830, the positioning mechanism of the device adjusts the relative position of the carrier to the camera (by adjusting the carrier, the camera, or both) so that when the camera captures the second image, the edge of the second image is adjacent to or aligned with the identified edge of the first image. Step 4840 means performing a set of analysis processing procedures on the combined image of the first and second images to determine one or more characteristics of the biological sample (eg, cell count). In some embodiments, when the edges of the second image are aligned with the edges of the first image, the two images can be used to compose a larger image. In some embodiments, the first and second images are simply from different perspectives. The second image may be positioned adjacent to the first image or randomly positioned such that the second image does not overlap the first image.

In some embodiments, the positioning mechanism may determine a plurality of fixed positions of the camera. In some embodiments, the positioning mechanism can determine multiple positions of the carrier. For example, a multi-axis mobile platform as shown in FIG. 49 can be used to adjust the position of the carrier and/or the position of the camera.

In some embodiments, multiple markers (such as the visual cues shown in FIG. 31 ) can be placed on the test device (such as on a movable platform) so that cameras can detect them. After the camera determines the location of the marker, the camera starts scanning using the marker as a starting point. The remaining marks serve as a guide for the camera scan path, thus allowing the test equipment to automatically adjust the camera to a fixed position to capture images from multiple perspectives. Scanning paths with markers can be random as long as no areas are scanned repeatedly. The scan paths can also be in a certain order (eg, clockwise or counterclockwise). For example, four markers can be used to designate four corresponding regions. The camera can capture each area sequentially or randomly along the markers without duplication. In some embodiments, the multiple axes 4901 of the stage allow manual or automatic adjustment of the carrier and/or camera along the X, Y and direction of the carrier stage.

In some embodiments, the positioning mechanism adjusts the relative position of the carrier to the camera so that when viewed from the camera, the plurality of images captured by the camera are sequentially clockwise or counterclockwise. For example, FIG. 50A shows an example manner in which images are acquired clockwise from the camera view. In some embodiments, the positioning mechanism adjusts the relative position of the carrier to the camera in such a way that when viewed from the camera, the plural Images are acquired through sequential scanning of the camera. FIG. 50B shows an example manner of sequential scanning to acquire images.

In some embodiments, the first and second images are combined before performing further image analysis. In some cases, the first and second images may overlap due to camera or carrier adjustments. The overlapping portions can be removed using image processing techniques to form a combined image.

As in Figures 50A-B, the edge of the first image may be the bottom edge of the first image and the edge of the second image may be the top edge of the second image. In some cases, the edge of the first image is a top edge of the first image and the edge of the second image is a bottom edge of the second image. Said edge of the first image may also be the left side of the first image and said edge of the second image may be the right side of the second image. Similarly, said edge of the first image may also be the right side of the first image and said edge of the second image may be the left side of the second image.

As described with respect to FIG. 16 , the test device calculates the concentration of sperm based on the volume of the sample that is taken by multiplying the sample holding area by the distance between the sample holding area and the bottom of the housing, however, due to manufacturing inaccuracies, the sample volume may not be the same as the distance between the sample holding area and the bottom of the housing may vary. In order to compensate for the aforementioned inaccuracies and determine the actual volume of the sample, the testing device may include a camera module with a focusing motor, such as a voice coil motor (VCM), a ceramic piezoelectric actuator, a focusing mechanism for a monocular camera or a servo motor mechanism for a microscope, etc. The focus motor is operable to drive the camera lens to adjust the camera focus. 51A-B illustrate an example of an adjustable lens for a camera module. In FIG. 51A, the lens is at an initial or preset position, corresponding to the first focal length of the lens. In Figure 5 IB, the lens is extended to its maximum length, corresponding to the second focal length of the lens. The two different positions of the lens form a distance L, which can be divided into a plurality of steps, and each step corresponds to a change in focal length. Therefore, by knowing the positions of the lenses of the two target objects, the distance between the two target objects can be obtained.

Fig. 52 shows an example of an arrangement for determining the actual volume of a sample contained in a carrier. The housing 5210 is placed on top of the carrier 5220 before the carrier 5220 is inserted to capture an image of the sample. A first visual cue 5217a (eg, as shown in FIG. 31 ) can be placed on the bottom of the housing 5210. The second visual cue 5217b may then be placed on a surface of the carrier 5220 that is in contact with or has been exposed to the sample of the carrier 5220 .

Before analyzing the biological sample in the carrier, the device first determines the first focus position of the camera module 5230 for the housing 5220 . This step is performed by adjusting the lens to focus on the first visual cue 5217a. The device can also adjust the lens to determine the second focus position of the cover 5210, so as to focus on the second visual prompt 5217b. The device can then determine the focus distance from these two focus positions and calculate the distance between the first surface of the housing 5210 and the second surface of the carrier 5220 . This processing procedure can be carried out at the configuration stage before analyzing a batch of samples (for example: the carrier and the cover in the same batch should use the equipment manufactured in the same batch so that they have the same characteristics). For more accurate sample reading, this procedure can also be performed during the use phase if each carrier and housing has different characteristics.

In a specific example, the lens of the camera module can support a focal length ranging from 50 μm to 550 μm. This range corresponds to the distance L between the two lens positions, as shown in Figures 51A-B. In some implementations, the distance L can be divided into 1024 steps (step 0, step 1, ... step 1023), each step corresponds to a specific focal length (that is, each step corresponds to (550-50)/1024=0.49 μm and has a different focal length). In the configuration phase, the test device first determines that the focus position of the first visual cue 5217a is 235 steps. The device then determines that the focus position of the second visual cue 5217b is 295 steps. The difference between these two steps (295-235)=60 steps corresponds to a focal distance difference of 60×0.49=29.4 μm, which also indicates the actual distance between the bottom surface of the housing and the top surface of the carrier. Through this distance and the area of the captured sample holding area, the actual volume of the sample can be determined.

In some examples, the housing 5210 and carrier 5220 can have multiple visual cues, located on top or bottom surfaces. For more accurate readings, the measurements can be made at different positions in the holding area set to execute. It is worth noting that the focal length and the ratio of said distance will vary with different lens designs. The ratio used in the above specific example is 1:1 (that is, the focal length of the lens is equal to the distance between the housing and the carrier). Various ratios between focal length and said distance can be supported, such as 1:1.2, 1:1.5, 1:2, etc.

Although some of the embodiments disclosed herein apply the disclosed technology to sperm testing, those skilled in the art will readily understand that the disclosed technology can be applied to testing various types of biological samples, such as semen, urine, sliding joint fluid, superficial tissue or cells, tumor cells, water samples, etc. In addition, the technology disclosed here can also be applied to various analytical processing procedures, such as sperm chromatin dispersion (Sperm Chromatin Dispersion, SCD) or terminal deoxyribose nucleotidyl transferase deoxyribonucleotidyl transferase dUTP nick end labeling (TUNEL) for detection of deoxyribonucleic acid (DNA) fragments. More specifically, in one or more implementations SCD can be performed, and the processor of the testing device described herein can be configured to use the captured images to determine the normalcy of sperm DNA fragments. In some examples, under the SCD test, the sperm head shows a large or medium halo (the size is known in the art), then the processor can determine that there is no DNA fragment problem in the tested sperm sample. On the contrary, if the sperm head is small, without halo or degraded halo, then the processor determines that the tested sperm sample has a DNA fragment problem. Additionally, TUNEL may be performed in one or more implementations. In one or more implementations, a processor of a test device described herein can be configured to detect apoptotic DNA fragments using the captured set of images. The processor can be used to identify one or more TUNEL-stained cells, thereby quantifying apoptotic cells and/or detecting excessive DNA fragmentation in individual cells.

In an example aspect, a device for detecting a biological sample includes a receiving mechanism for receiving a carrier. The carrier includes a holding area configured to carry a biological sample. The device includes a camera module configured to capture collective images of the holding area. The device also includes a processor configured to use the camera module to A set of images is captured to identify visual cues on the carrier, and a set of analysis processes are performed on the set of captured images based on the recognition of the visual cues. The identification of the visual cue includes: verifying whether the holding area contains a biological sample according to the way the visual cue is displayed in the captured set of images, and selectively causing the processor to execute a set of analysis processing procedures on the captured set of images according to the result of the verification.

In some embodiments, the processor executes the set of analysis processing procedures on the captured set of images only after confirming that the holding area carries the biological sample. In some embodiments, the processor does not execute the set of analysis processing procedures on the captured set of images if it is not confirmed whether the holding area carries the biological sample. In some embodiments, the processor may also display a predetermined signal or flag related to the failure to verify whether the holding area contains a biological sample.

In some embodiments, the manner in which the visual cue is displayed includes optical distortion of the visual cue. In some embodiments, the optical distortion produced by the visual cue corresponds to a difference in refractive index between the biological sample and air. In some embodiments, verifying whether the holding region carries a biological sample includes comparing an optical distortion of the visual cue with a distortion threshold, where the distortion threshold represents a degree of optical distortion that may be indicative of the presence of the biological sample in the holding region. In some embodiments, the process of verifying whether the holding area carries a biological sample includes comparing the difference between the visual cue and the stored visual cue set image, and if the difference is lower than a preset threshold, it proves that the holding area has a biological sample.

In some embodiments, the processor is configured to retrieve the stored images of the set of visual cues during the configuration phase without any biological sample on the carrier. In some embodiments, the visual cue is located in or adjacent to a retention area on the carrier. In some embodiments, the visual cue is recognized when the visual cue is present in a predetermined shape or at a predetermined location. In some embodiments, the visual cue includes a preset configuration of a plurality of visual markers.

In some embodiments, the device includes a housing. The components of the device are all encapsulated within the housing. The exterior size of the shell is less than 27000 cubic centimeters. In some specific instances, the device Also included is a display housed inside the housing. The processor is configured to display the final result of the determination on the display after obtaining the final result. In some embodiments, the display is configured to display a notification based on a result of the verification. In some embodiments, the notification includes a signal or flag indicating that the biological sample has not been provided. In some embodiments, the processor is further configured to determine a biochemical property of the biological sample using the set of analytical processing procedures.

In another example aspect, an automated test device for testing multiple view angle analysis of a biological sample includes a receiving mechanism to receive a carrier configured to carry or have been exposed to the biological sample. The device includes a camera module configured to capture a plurality of images of the holding area. The device also includes a processor configured to use the camera module to adaptively select an analysis algorithm based on the plurality of images of the holding area, the analysis algorithm is suitable for the movement characteristics of the biological sample to be tested, and execute a set of analysis processing procedures corresponding to the selected analysis algorithm on the captured plurality of images to obtain relevant analysis results of the biological sample.

In some embodiments, the mobility characteristic remains substantially static or substantially dynamic. In some specific examples, the processor will adaptively select the analysis algorithm according to the following steps, the steps include determining the amount of change between the first image and the second image in the plurality of images, and selecting a static algorithm or a dynamic algorithm according to whether the determined amount of change is less than or greater than a threshold. In some embodiments, the amount of change is determined according to the change rate of movement of the detectable target in the biological sample.

In some specific examples, the processor will adaptively select an analysis algorithm according to the following steps. The steps include: determining the amount of change between the first image and the second image in the plurality of images, comparing the determined amount of change with a threshold, and selecting an analysis algorithm suitable for the motion characteristic according to the comparison result between the determined amount of change and the threshold. In some embodiments, the analysis algorithm is a static algorithm or a dynamic algorithm. In some embodiments, the threshold is a characteristic of whether the biological sample is substantially static or dynamic. In some embodiments, the processor is configured to use an analysis algorithm to determine Determine the mobility of biological samples. In some specific examples, when the determined variation is less than a threshold, the selected algorithm is a static algorithm. In some specific examples, when the determined variation is not less than the threshold, the selected algorithm is a dynamic algorithm.

In some embodiments, the processor is configured to determine the trajectory of the biological sample using a dynamic algorithm. In some specific examples, the acquisition of the first image and the second image must be separated by at least a predetermined period of time in sequence. In some specific examples, the preset time ranges from 0.04 seconds to 10 seconds. In some embodiments, for a given number of image acquisitions in sequence, both the first image and the second image are acquired separately. In some specific examples, the sequentially given number of images acquired ranges from 2 to 600 images. In some specific examples, the device further includes a casing, wherein the receiving mechanism, the camera module, and the processor are all packaged in the casing, and the outer size of the casing is less than 27,000 cubic centimeters.

In another example, an automated testing device for testing multiple view angle analysis of a biological sample includes a receiving mechanism to receive a carrier including a holding area configured to carry or have been exposed to the biological sample. The device includes a camera module configured to capture a plurality of images of the holding area, including a first image and a second image, and a positioning mechanism operable to adjust the relative positions of the carrier and the camera. The device also includes a processor configured to utilize the camera module to identify an edge of the first image, cause the positioning mechanism to adjust the relative positions of the carrier and the camera so that when the camera acquires a second image, an edge of the second image is adjacent to the identified edge of the first image or to perform a set of analysis processing procedures on the combined image of the first and second images to determine one or more characteristics of the biological sample.

In some specific examples, the positioning mechanism adjusts the relative position of the carrier and the camera in such a way that when viewed from the camera, a plurality of images are sequentially acquired by the camera in a clockwise or counterclockwise direction. In some specific examples, the positioning mechanism determines the relative position of the carrier and the camera based on a plurality of marks detected by the camera. In some specific examples, the way the positioning mechanism adjusts the relative position of the carrier and the camera is: When observing from the camera, the camera acquires multiple images in the order of sequential scanning. The processor may also be configured to combine the first and second images to form a combined image. In some embodiments, overlapping portions of the first and second images are not included for analysis processing of the combined images. In some embodiments, the one or more characteristics of the biological sample include cell number.

In some specific examples, the edge of the first image is at the bottom of the first image, and the edge of the second image is at the top of the second image. In some embodiments, the edge of the first image is at the top of the first image, and the edge of the second image is at the bottom of the second image. In some specific examples, the edge of the first image is on the left side of the first image, and the edge of the second image is on the right side of the second image. In some specific examples, the edge of the first image is on the right side of the first image, and the edge of the second image is on the left side of the second image.

In some specific examples, in order to adjust the relative position of the carrier and the camera, the positioning mechanism adjusts the carrier to a next position, so that the camera can acquire subsequent images. In some specific examples, in order to adjust the relative position of the carrier and the camera, the positioning mechanism adjusts the camera to a next position, so that the camera can acquire subsequent images. In some specific examples, after the camera acquires the first image, the processor automatically adjusts the relative position of the carrier and the camera.

In some embodiments, the positioning mechanism is configured to automatically adjust the camera to a plurality of fixed positions. In some embodiments, the positioning mechanism includes a multi-axis motion platform configured to adjust the carrier or camera to a plurality of positions. In some embodiments, the multi-axis mobile platform is configured to enable manual adjustment of the carrier position. In some embodiments, the multi-axis motion platform is configured to automatically adjust the position of the carrier. In some embodiments, the device further includes a housing. The receiving mechanism, the camera module and the processor are all packaged in the housing, and the outer dimension of the housing is 27,000 cubic centimeters.

In another example, an automatic testing device for testing multiple viewing angles of a biological sample includes: a receiving mechanism for receiving a carrier, wherein the carrier includes a holding area, the The holding area is configured to carry or have been exposed to the biological sample. The device includes a camera module configured to capture collective images of the holding area. The camera module includes an operable focus motor to adjust the focus of the camera. The device includes a processor configured to utilize a camera module to determine a volumetric characteristic of a holding region based on operation of a focus motor and to perform an analysis process on at least a portion of the captured holding region images to determine one or more characteristics of the biological sample. One or more properties of the biological sample are adjusted by the processor based on the determined retention region volume properties.

In some embodiments, the processor is configured to focus on different positions of the holding area by operating the focus motor to determine the volumetric properties of the holding area. In some embodiments, the processor is configured to simultaneously estimate the depth of the retention region when determining the volumetric properties of the retention region. In some embodiments, the processor is configured to perform calculations to convert the estimated depth of the retention region into volumetric properties of the retention region.

In some embodiments, the processor is configured to determine the volumetric properties of the holding area by focusing the camera on one of the housing or the holding area to form a first focus, measuring a first depth of the first focus, focusing the camera on the other of the housing or holding area to form a second focus, and measuring a second depth of the second focus. In some embodiments, the housing and the holding area each include visual indicia for the camera to focus on. In some embodiments, the underside of the housing is also marked with visual markings. In some embodiments, the visual indicia is placed on a surface of the holding area that is in contact with or has been exposed to the biological sample. The visual indicia can be made microscopic in size.

In some embodiments, the first and second depths are measured based on the operation of the focus motor. The first depth and the second depth can be measured according to how many steps the focus motor operates when reaching the first focal point and the second focal point from the preset starting point. In some specific examples, the total travel (travel) available for focus adjustment is preset, and the total available (available) steps correspond to the available Total travel for focus adjustment. In some embodiments, the focus motor assembly includes a voice coil motor, a ceramic piezoelectric actuator, and a focus mechanism of a monocular camera or a servo motor mechanism of a microscope. In some embodiments, the one or more characteristics of the biological sample also include the concentration of the biological sample. In some embodiments, the biological sample is semen.

In some embodiments, during the configuration phase, volumetric properties of the holding area are determined. In some embodiments, during normal use, analysis and processing procedures on the biological sample are performed. In some embodiments, the device further includes a casing, the receiving mechanism, the camera module and the processor are packaged in the casing, and the outer size of the casing is less than 27,000 cubic centimeters.

It will be apparent to those skilled in the art that various modifications and changes can be made in the structure of this invention without departing from the scope or spirit of the invention. In view of the foregoing, it is intended that the present invention covers the modifications and variations of the present invention, as long as they fall within the scope of the following claims and their equivalents.

2205: Test strip device

2210A: outer cover

2210B: Magnification component

2215A: The first holding area

2215B: Second holding area

2230A: The first camera module

2230B: Second camera module

2240A: light source

2240B: light source

Claims (18)

An automatic test device for analysis of multiple viewing angles, the device comprising: a receiving mechanism to receive a carrier, wherein the carrier includes a holding area, wherein the holding area is configured to carry the biological sample or has been exposed to the biological sample; a camera module, which is configured to capture a plurality of images of the holding area, and the plurality of images includes a first image and a second image; a positioning mechanism, the positioning mechanism is operable to adjust the relative position of the carrier to the camera module; a processor, the processor is configured to use the camera module Combining: identifying the edge of the first image; causing the positioning mechanism to adjust the relative position of the carrier to the camera module so that when the camera module acquires the second image, the edge of the second image is aligned with the identified edge of the first image; and executing a set of analysis processing procedures on an image at least partially including the first image and the second image to determine one or more characteristics of the biological sample; Cubic centimeters. The device according to claim 1, wherein the positioning mechanism adjusts the relative position of the carrier to the camera module, so that when viewed from the camera module, the plurality of images are captured by the camera module in a predetermined order. The device according to claim 1, wherein the positioning mechanism adjusts the relative position of the carrier to the camera module, so that when viewed from the camera module, the plurality of images are sequentially captured by the camera module in a clockwise or counterclockwise direction. The device according to claim 1, wherein the positioning mechanism adjusts the carrier The relative positions of the camera modules are such that when viewed from the camera modules, the plurality of images are captured by the camera modules in a sequentially scanned order. The device according to claim 1, wherein the positioning mechanism adjusts the relative position of the carrier to the camera module so that when viewed from the camera module, the plurality of images are randomly captured by the camera module. The device of claim 1, wherein the processor is further configured to combine the first image and the second image to form the image. The device according to claim 1, wherein the analysis and processing program of the image does not include overlapping portions of the first image and the second image. The device of claim 1, wherein the one or more characteristics of the biological sample include cell number. The device according to claim 1, wherein the edge of the first image is at the bottom of the first image, and the edge of the second image is at the top of the second image. The apparatus according to claim 1, wherein the edge of the first image is at the top of the first image, and the edge of the second image is at the bottom of the second image. The device according to claim 1, wherein the edge of the first image is on the left side of the first image, and the edge of the second image is on the right side of the second image. The device according to claim 1, wherein the edge of the first image is on the right side of the first image, and the edge of the second image is on the left side of the second image. The device according to claim 1, wherein in order to adjust the relative position of the carrier and the camera module, the positioning mechanism adjusts the carrier to a next position, so that the camera module can acquire subsequent images. The device according to claim 1, wherein in order to adjust the relative position of the carrier and the camera module, the positioning mechanism adjusts the camera module to the next position, so that the camera The module fetches subsequent images. The device according to claim 1, wherein after the camera module acquires the first image, the processor automatically adjusts the relative position of the carrier and the camera module. The device of claim 1, wherein the one or more characteristics of the biological sample also include a concentration of the biological sample. The device of claim 1, wherein the biological sample is semen. A controller for controlling an automatic testing device for multiple viewing angle analysis of a test biological sample, the device comprising: a receiving mechanism for receiving a carrier, wherein the carrier includes a holding area, wherein the holding area is configured to carry the biological sample or has been exposed to the biological sample; a camera module configured to capture a plurality of images of the holding area, and the plurality of images includes a first image and a second image; a positioning mechanism operable to adjust the relative position of the carrier to the camera module; wherein the controller is configured to utilize the camera module to: identify edges of the first image; cause the positioning mechanism to adjust the relative position of the carrier to the camera module so that when the camera module acquires the second image, the edges of the second image are aligned with the identified edges of the first image; and execute a set of analysis processing procedures on an image at least partially comprising the first image and the second image to determine one or more characteristics of the biological sample; The exterior size is less than 27,000 cubic centimeters.

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