TW201514839A - MEMS-based proximity sensor device and method - Google Patents

Abstract

A portable proximity device and method of operation thereof. The method for proximity detection implemented on a portable device can include determining an initial perturbation data, a tracking point data, and a stable position data with a physical sensor of the portable device. The initial perturbation data can include previous state data and current state data. The tracking point data can include one or more track data. An action to be performed can be determined, by a processor within the portable device, based on the initial perturbation data, the tracking point data, and the stable position data. The portable proximity device can include a physical sensor and a processor configured to perform these steps.

Description

Micro-electromechanical system (MEMS) based proximity sensor device and method Cross-reference to related applications

The present application claims priority to the patent application in the following application: U.S. Provisional Application No. 14/194,468, filed on Feb. 28, 2014, and U.S. Patent Application Serial No. No. 61/829,115, the disclosure of which is hereby incorporated by reference in its entirety in its entirety in its entirety in the the the the the the

Research and development of integrated microelectronic devices has continued to make amazing progress in CMOS and MEMS. CMOS technology has become the main manufacturing technology for integrated circuits (ICs). Microelectromechanical systems (MEMS) based sensors can be interfaced with IC technology to implement several progressive sensor applications. With the growing use of integrated MEMS-CMOS devices, methods and systems for testing such integrated devices have become critical to ensuring product reliability.

The present invention relates to MEMS (Micro Electro Mechanical Systems) devices.

In one embodiment, the invention includes a MEMS-based proximity sensor device and method of operation. Proximity sensors are commonly used in smart phone devices (especially those with a touch screen). One of the main functions of the proximity sensor in this device is to disable the accidental touch event. The most common scenario with this proximity sensor is the ear touch screen and generates a touch event when the user answers a call.

A method for proximity detection implemented on a portable device can include A physical sensor of the portable device determines an initial disturbance data, a tracking point data, and a stable position data. The initial disturbance data may include previous status data and current status data. The tracking point data may include one or more tracking data. One of the actions to be performed may be determined by a processor in the portable device based on the initial disturbance data, the tracking point data, and the stable position data. The portable proximity device can include a physical sensor and a processor configured to perform one of these steps.

A number of benefits over conventional techniques are achieved with the present invention. These benefits include a MEMS accelerometer that can be configured as a virtual proximity sensor and used in conjunction with a service resident program as an alternative to the proximity sensor hardware and integrated circuitry. The accelerometer-based proximity sensor can be implemented in portable computing devices, such as smart phones and tablets, to detect user gestures. Particular embodiments and methods of use may vary depending on the application.

In various embodiments, one or more of the magnitude changes in the movement of the mobile device may be predetermined. One such example of a variable curve can include a mobile device or the like to move and maintain in a stable upward position from one of the horizontal or vertical positions. This scalar curve can be based on a user picking up their phone, moving the phone towards its head, and then placing the call next to its head. In various embodiments, subsequent movements of the mobile device via a MEMS sensor or the like are compared to one or more quantitative curves. In some embodiments, a status flag or the like can be set when there is an approximate match. Subsequently, an operating system program (eg, a resident program) can perform an action in response to an indicator (eg, turning off a display, hanging up a phone call, or the like).

The various additional objects, features and advantages of the present invention will be more fully understood from the description of the appended claims.

1 illustrates a simplified one for initial motion detection in accordance with an embodiment of the present invention. Formula.

2 illustrates a simplified formula for tracking point detection in accordance with an embodiment of the present invention.

3 illustrates a simplified formula for sensor data inspection in accordance with an embodiment of the present invention.

4 illustrates a simplified formula for sensor data inspection in accordance with an embodiment of the present invention.

Figure 5 illustrates a simplified formula for sensor data inspection in accordance with an embodiment of the present invention.

6 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention.

7 illustrates a simplified block diagram of a MEMS proximity sensor system in accordance with an embodiment of the present invention.

8 illustrates a simplified block diagram of a MEMS proximity sensor system in accordance with an embodiment of the present invention.

9 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention.

10 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention.

11 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention.

Figure 12 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention.

The present invention relates to the use of integrated circuit (IC) and MEMS (Micro Electro Mechanical Systems) devices. More specifically, embodiments of the present invention are provided for use in mobile phones, tablets, hands A method and structure for holding an integrated MEMS sensor device implemented on a computer, a magnetic field sensor, and the like.

In one embodiment, the invention includes a MEMS-based proximity sensor device and method of operation. One embodiment of each of the steps in a method of operating a MEMS-based proximity sensor is set forth below. The method can include using a virtual proximity sensor and a service resident program during a telephone call as an alternative to a proximity sensor hardware IC. In one example, the virtual proximity sensor can be used to "turn on" or "turn off" a display of a mobile phone, reducing a backlight or the like. Other electronic devices, touch screen devices, and the like can also be used. In one embodiment, when a user approaches a handset during a phone call, the screen backlight of a mobile phone is turned off. On the other hand, the screen will be turned on immediately after the user is away, and the screen will be turned off when the user's ear approaches.

In a particular embodiment, the MEMS-based proximity sensor device can include an accelerometer-based proximity sensor and the method of operation can include utilizing accelerometer sensor data for two-phase detection The gesture of the person and the movement of the earpiece, and only a proximity event is obtained when the proximity change (NEAR to FAR or FAR to NEAR). Accelerometer data can be used by a service resident program to calculate the proximity values associated with such proximity changes.

Step 1: Detect movement at the beginning - detect gestures from anywhere to near the ear, which brings the X, Y, and Z axis values into the gesture detection model. And compare the X, Y, and Z axis values ("CurrentX", "CurrentY", and "CurrentZ") with their initial values before moving ("PreviousX", "PreviousY", and "PreviousZ") and at the first move The value captured immediately. If it senses that the device is beginning to move, then two or more points of the (x, y, z) axis value during the tracking of the movement near the ear from anywhere (ie, from the front of the body to the ear) sampling. As an example, the two or more points may comprise any integer greater than two. In a particular embodiment, the two or more points may comprise 5 consecutive points. Those skilled in the art will recognize that the various quantities of points depend on the particular embodiment and application.

1 illustrates a simplified formula for initial motion detection in accordance with an embodiment of the present invention. The "SENSITIVITY" value is the resolution of a MEMS device such as an accelerometer, a magnetic field sensor, a gyroscope sensor, and the like. "xShakeParm", "yshakeParm" and "zShakeParm" are the parameters specified at the beginning of the shake detection.

It is assumed that the device starts moving when the absolute value of the difference between "CurrentX" and "PreviousX" is greater than a certain ratio (ie, "SENSITIVITY" / "xShakeParm"). In various embodiments, the pass criteria can be based on the difference in X, Y, or Z-axis values, or a combination thereof. Of course, other variations, modifications, and alternative embodiments can be used.

Step 2: Detect any tracking point from anywhere to the ear - after successful in step 1, then sample two or more consecutive points of the (x, y, z) axis data to determine the device from anywhere Move to the vicinity of the ear. The difference between the first of two or more sampling points during the tracking period ("TrackData[1 ^st ]") and the last point ("TrackData[last]") will be compared. In various embodiments, it is estimated that it should pass on any of the X, Y, or Z axes, or a combination thereof (eg, X and Y, Y and Z, X and Z, or X, Y, and Z). In a particular embodiment, the estimate should pass on both the X and Z axes ([Xaxis], [Zaxis]).

2 illustrates a simplified formula for tracking point detection in accordance with an embodiment of the present invention. This formula describes several parameters. "SENSITIVITY" is the resolution of the device IC. "xMoveParm", "yMoveParm" and "zMoveParm" are based on the parameters of the movement criteria. Here, it is assumed that the device actually moves on the X, Y, and Z axes while passing the criteria of step 1, which results in sampling of two or more consecutive points of the data inspection of step 2. If this data check is passed on X, Y, and Z (or any combination of inspections is passed on the X, Y, and Z axes), then step 3 is performed to verify the final position of the device.

Step 3: Check the stable position of the sensor data - during the user's movement, check the position of the sensor data by using the last point held by step 2. 3 through 5 illustrate simplified formulas for sensor data inspection in accordance with an embodiment of the present invention. Compare the last point of the motion tracking with one of the X, Y, and Z test boundaries to get the best proximity. Specific parameters for the stable position check phase of the sensor data include "XPositionParm", "YPositionParm" and "ZPositionParm". This inspection step may include three steps of examining the data for each axis (X, Y, Z), which are shown in Figures 3, 4 and 5, respectively.

It is assumed that the last point of the X, Y, Z sensor data is located near a range near the ear when passing three criteria with the designed parameters and offset. After passing, the service resident program will immediately switch the proximity value under the calculated proximity sensor driver. The system will turn on or off based on the proximity value (which is NEAR to FAR or FAR to NEAR).

In various embodiments, when the points tracked in steps 1 and 2 are similar to an arc or a curve from an initial position, this may instruct the user to pick up a mobile device that implements an embodiment of the present invention. Additionally, when the final stable position of the device in step 3 is in an upright and/or tilted position relative to gravity, this may instruct the user to hold the mobile device next to its head. Thus, in various embodiments, based on the tracking point and the final/stable position, it can be inferred that the particular combination of movements represents the user answering a telephone call on their mobile device (eg, picking up a mobile device and positioning the mobile device as Next to its face). In such a combination of movements, embodiments of the present invention may indicate that the mobile device is in close proximity to the user's face (e.g., NEAR), which causes the mobile device to turn off the display.

In various embodiments, although the mobile device is in an approximately stable position, the mobile device can maintain a NEAR proximity value and can maintain display off, low backlight, backlight off, or the like. Subsequently, embodiments of the present invention can switch the proximity value to the FAR by monitoring the tracking point as the mobile device moves away from the stable position, as discussed above. Therefore, the display can be restored.

In some embodiments, different MEMS sensors can be used to determine motion data. For example, in one embodiment, a 3-access accelerometer can be used; in another example, A gyroscope is used; in still other embodiments, a sensor such as a pressure sensor or a magnetometer can be used.

6 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention. This flowchart represents a particular embodiment of implementing one of the steps 1 through 3 previously set forth with respect to Figures 1 through 5. In this case, the initial movement check of step 1 and the tracking point detection of step 2 are combined with respect to one of the inspections on the X-axis and the Z-axis. At the same time, the method is shown as sampling n consecutive sensor data during the motion tracking, where n is an integer greater than one of zero.

In one embodiment, the invention includes a portable proximity sensor and method of operation thereof. This related device and method may be referred to as a "CallSense" device and method or "CallSense 1.0". The method for proximity detection implemented on a portable device can include determining an initial disturbance data, a tracking point data, and a stable position data by means of a physical sensor of the portable device. The initial disturbance data may include previous status data and current status data. The tracking point data may include one or more tracking data. One of the actions to be performed may be determined by a processor in the portable device based on the initial disturbance data, the tracking point data, and the stable position data.

In a particular embodiment, the method can also include comparing the difference between the previous state data and the current state data with one or more first thresholds. Each of the one or more first thresholds can include a ratio between a sensitivity parameter and a shake detection parameter, as set forth with respect to Figures 1 and 2. The initial disturbance data may include X-axis disturbance data and Z-axis disturbance data, as shown in FIG. It can also contain a Y-axis disturbance data. In this case, the one or more first thresholds include an X-axis first threshold and a Z-axis first threshold. The X-axis first threshold may include a ratio between the sensitivity parameter and an X-axis shake detection parameter. The Z-axis first threshold may include a ratio between the sensitivity parameter and a Z-axis shake detection parameter. Additionally, a Y-axis first threshold can be implemented, the Y-axis first threshold including a ratio between the sensitivity parameter and a Y-axis shake detection parameter. Of course, there may be other changes Modifications, modifications and alternative forms.

In a particular embodiment, the method step of determining tracking point data includes sampling two or more consecutive points in the (x, y, z) axis data. The difference between the first point in the (x, y, z) axis data of the continuous point and the last point in the (x, y, z) axis data can be compared to one or more second threshold values. The one or more second thresholds can include a ratio between a sensitivity parameter and a movement parameter. The one or more second thresholds can include an X-axis second threshold and a Z-axis second threshold. The X-axis second threshold may include a ratio between the sensitivity parameter and an X-axis movement parameter. The Z-axis second threshold may include a ratio between the sensitivity parameter and a Z-axis movement parameter. A Y-axis second threshold can also be implemented, wherein the Y-axis second threshold includes a ratio between the sensitivity parameter and a Y-axis movement parameter. In a particular embodiment, the threshold of the initial perturbation data and the tracking point data may comprise a combination of one of the X, Y, and Z first or second thresholds.

In addition, the last point in the (x, y, z) data from one or more tracking data can be compared to one or more third thresholds and one or more fourth thresholds. The one or more third thresholds can include a ratio between the sensitivity parameter and a position parameter. For example, the one or more third thresholds can include an X-axis, a Y-axis, and a Z-axis third threshold. Each of these third thresholds may each include a ratio between the sensitivity parameter and an X-axis, Y-axis, or Z-axis position parameter. Similarly, the one or more fourth thresholds may include an X-axis, a Y-axis, and a Z-axis fourth threshold, wherein each of the values may include a sensitivity parameter and an X offset value, respectively. A ratio between the sum of the Y offset value or a Z offset value and a Z-axis positive position parameter. The method can include whether the first perturbation data exceeds one or more first thresholds, whether the tracking point data exceeds one or more second thresholds, and whether the stable location data exceeds one or more third and fourth The limit value determines one of the actions to be performed. Of course, there may be other variations, modifications, and alternatives.

The portable proximity device can include a physical sensor and a processor configured to perform one of these steps. The portable device can include a configuration to determine initial disturbance data, tracking points One of the data and stable location data entity sensors. The physical sensor can include an accelerometer, a gyroscope sensor, a magnetic field sensor or other MEMS physical sensor, or a combination thereof. The physical sensor can be coupled to a processor that can be programmed to determine an action to perform based on such information and whether it exceeds a previously stated threshold.

7 illustrates a simplified block diagram of a MEMS proximity sensor system in accordance with an embodiment of the present invention. This diagram shows the interaction between the MEMS hardware and the software interface of a portable device operating on an Android operating system. The sensor is configured through the Linux device driver and controlled by the service resident program. The sensor operates and communicates to the Android native interface of the Android framework through the Android HAL (hardware abstraction layer). Other frameworks and interfaces can be used in implementing various embodiments of a portable device of a MEMS proximity sensor system.

In one embodiment, the present invention is directed to a virtual proximity sensor algorithm that is one of the solutions for replacing a proximity sensor hardware. The algorithm applied as a proximity sensor system and its method of operation can be referred to as "CallSense 2.0." According to an embodiment, there are two emphasized hints about this algorithm. First, the algorithm demonstrates the high frequency and high resolution of the accelerometer data that tracks the pick-up/hand-off gesture of the handheld device (for a sensor with a software 50Hz sampling rate, 14-bit resolution and +/-8g range) )collect. Second, using the Close/Far Away state as a function of the hardware proximity sensor, the algorithm considers the end result of the accelerometer and touch panel proximity signals as one of the proximity states.

8 illustrates a simplified block diagram of a MEMS proximity sensor system in accordance with an embodiment of the present invention. This diagram shows the interaction between a "CallSense software package" (referring to an embodiment of the invention) and a computer system framework. The implementation of the CallSense method and the system configured for the CallSense method may use the "CallSense 1.0", "CallSense 2.0" embodiments, or other variations of such embodiments as would be recognized by those skilled in the art. In this system, a portable device's MEMS hardware (shown as accelerometer hardware and touch hardware) operates on an Android operating system. Sensor, accelerometer and touch The control hardware is configured through a Linux device driver, and the sensors, accelerometers, and touch hardware can be controlled by a service resident program. As shown, the CallSense software package can be combined with multiple levels of systems (including the Linux device driver level, the Android HAL level via a CallSense algorithm, and the device driver at the Android application level via a CallSense Background APK). Consider touch)) interaction. Other frameworks and interfaces can be used in implementing various embodiments of a portable device of a MEMS proximity sensor system.

Touch panel and accelerometer detection Close state detection has its own weakness. The touch panel can be affected by temperature, humidity, and stress (deformation). The accelerometer only supports one of the standard gestures of "Pickup" and "Respond to Call" (running, lying down, shaking in, etc. will have an impact). Operation by combining both the sensor hardware and the method of the present invention benefits from a two-way advantage to improve Close detection accuracy. Other benefits may include saving hardware proximity sensor cost in the handheld BOM list and improving the accuracy of the Accelerometer only (CallSense 1.0) solution.

9 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention. This flow chart may represent one of the main flow charts for one of the methods for operating a proximity sensor system. The method begins by initializing a proximity sensor system, waiting for a "phone call status" to become active, achieving an accelerometer resident program, and enabling a touch panel proximity detection procedure. The method then involves waiting for an application to request a proximity state, obtaining an accelerometer resident program proximity state, and obtaining a touch panel proximity state.

Then, encounter a first query: a "Check the phone call status is valid?" program. If the telephone call status is not valid, the method disables the accelerometer resident program and returns to the "waiting for the call state is valid" step through a first loop. If the phone call status is valid, a second query "Accelerator resident program close state is Close?" or "Touch panel proximity state Close?" is encountered. If any proximity state is Approaching, the method returns a "Close" value, and if both states are not close, an "Away" value is returned. After the value is passed back, the method returns to the method step of the application waiting for the requesting proximity state through a second loop.

In an embodiment, the invention may include a method of operating a proximity sensor system. The method can include initializing a proximity sensor system, waiting for an active state, achieving a first sensor service resident program, and implementing a second sensor service resident program. The proximity sensor system can include a first sensor device and a second sensor device, and the like can be an accelerometer and a touch panel, respectively. The active state can be associated with a telephone call state. The first sensor service resident program and the second sensor service resident program may be associated with the first sensor and the second sensor, respectively. The method can then perform three different program loops: the first loop program can include: receiving a status request from an application, and capturing a first sensor status from the first sensor service resident program, since The second sensor service resident program captures a second sensor state, receives an active state, determines a proximity state based on the first sensor state or according to the second sensor state, and returns a proximity value.

The second loop program may include: receiving a status request from an application, capturing a first sensor status from the first sensor service resident program, and capturing a second from the second sensor service resident program The sensor state receives an active state, determines a distant state according to the first sensor state and according to the second sensor state, and returns a distant value.

The third loop program may include: receiving a status request from an application, capturing a first sensor status from the first sensor service resident program, and capturing a second from the second sensor service resident program The sensor state, receiving an inactive state, deactivating the first sensor service resident program, waiting for an active state, reaching a first sensor service resident program, and reaching a second sensor service resident program.

10 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention. This flow chart can be used to operate a proximity One of the methods of the sensor system is one of the flowcharts of the accelerometer tracking detection section. The method begins by initializing a proximity sensor system, initializing a buffer, setting a gestCount value to zero, and setting a proximity state to "Away." The method can include recording an accelerometer data and making an inquiry as to whether a data record is sufficient and sufficient (i.e., whether (gestCount >= 6)). If the query is not met, the gestCount is incremented and the method loops back to the record of the accelerometer data.

If the inquiry is satisfied, another inquiry about motion detection is made. This inquiry may involve determining whether one of the standard deviations (i.e., stdevX, stdevY or stdevZ) of any of the axial measurements exceeds a predetermined value (such as 100). If this inquiry is not met, the buffer is cleared and gestCount is set to zero. If the query is satisfied, the method can proceed to increase the gestCount and record the accelerometer data.

Another inquiry may be made as to whether the data record is sufficient and sufficient (i.e., whether (gestCount>=15)). If this query is not met, the method loops back to incrementing gestCount and recording Accdata. If the inquiry is satisfied, another inquiry about motion detection is made. The query may include detecting a steady condition from one of gestCount-9 to gestCount and determining whether the standard deviation of the measurements on all axes is less than another predetermined value (ie, stdev < 70). If this query is not met, the method loops back to incrementing gestCount and recording Accdata.

Another query can then be made: this inquiry checks if a pick gesture analysis is registered as true. If the query is not satisfied, the method loops back to: clearing the buffer, setting gestCount to 0, and starting at the beginning of recording Accdata. If the inquiry is satisfied, the method proceeds to another inquiry as to whether the check position response position is true. If the query is not satisfied, the method also loops back to: clear the buffer, set gestCount to 0, and start recording Accdata. If the inquiry is satisfied, the method proceeds to a new state.

In this new state, a close state is set, a P_status value is set to 1, the buffer is cleared, and gestCount is set to zero. The method proceeds to record Accdata and check Whether gestCount is greater than or equal to another value (ie, 10). If this comparison is not met, the gestcount is incremented and the method loops back to recording Accdata in this new state. If the comparison is satisfied, the method proceeds to check the position response position. If the query returns false, set a far away state, set P_status to 0, and the method loops back to: clear the buffer, set gestCount to 0, and record Accdata from the top of the flowchart. If the inquiry is returned to the true, another motion detection inquiry is made. If any of the measured standard deviations of any axis exceeds another value (ie, stdev>200), then set the far state, set P_status to 0, and the method loops back to: clear the buffer, The gestCount is set to 0, and the Accdata is recorded from the top of the flowchart. If the query returns false, the method returns to: setting a proximity state, setting P_status to 1, clearing the buffer, setting gestCount to 0, and recording Accdata in the lower program loop.

In an embodiment, the invention may include a method of operating a proximity sensor system. The method can include initializing a proximity sensor system, initializing a buffer, setting a count value to zero, and setting a proximity state to "Away." The proximity sensor system can include a first sensor device and a second sensor device that can be respectively an accelerometer and a touch panel. The method can include performing a detection gesture and recording a sensor data program that records one of standard deviations along a shift of X, Y, and Z axes. The program is engaged in increasing the count of a gesture count until the count exceeds a first count threshold and the standard deviation on any axis exceeds one of the first deviation thresholds.

The method includes: following a previously discussed program loop, a second program loop comprising increasing the count until the count value exceeds a second count threshold and the standard deviation across all axes is less than one The second offset value detects a steady state. The method then determines that a gesture check is true and a location check is true.

The method includes a third program loop after the program loop discussed next, the third program loop includes setting a detection state to be close, clearing the buffer, and setting the count to zero. Perform the recording sensor data program again and increase the count until the count More than a third threshold. The executed record sensor data program continues until it is determined that a position check is true and the standard deviation measured on any axis is greater than a third deviation threshold. After that, set the detection status to be away. This method clears the buffer and sets the count to 0, and the method restarts from the top of the program flow.

11 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention. This flow diagram may represent one of a flow chart of one of the gesture checks for operating one of the proximity sensor systems. The method includes a series of queries relating to a condition such as a first deviation value (i.e., 250) of one or more of the X, Y, and Z axes. The queries may include checking whether the difference between a maximum data and a minimum data is less than a data difference threshold (i.e., 2.5 g). The queries may also include checking whether one of the standard deviations measured on any of the axes is divided by whether a gesture count is less than a deviation gesture ratio (i.e., 30). A start and stop position check may be included wherein the recorded data of one or more of the axes is less than a dead threshold (i.e., -500 mg). A full motion loop check can be included wherein the number of loops on any of the measured axes is greater than a full loop threshold (i.e., 2). At the same time, a half cycle check can be included in which the number of cycles on any of the measured axes is checked to be greater than one half cycle threshold (i.e., 1). In addition, an energy ratio check may be included, wherein it is determined whether a ratio of a measured standard deviation of one of the first axes to a measured standard deviation of one of the second axes exceeds a first energy ratio (ie, , 66), or inversely (2 ^nd stdev / 1 ^st stdev) whether it exceeds a second energy ratio (ie, 166).

In a particular embodiment, the queries can be ordered in a particular manner. In the case of a full mobile loop check, a false return causes the method to jump to the energy ratio check. One of the false returns on the half cycle check can also lead to an energy ratio check. Otherwise, each of the questions listed above can be followed by a true return, where the true return of the energy ratio check results in an overall truth or a return of one of the values. All other false returns to other inquiries may result in a general false or no return.

Figure 12 illustrates a simplified flow diagram of one method for operating a MEMS proximity sensor device in accordance with an embodiment of the present invention. This flow chart may represent a flow chart of one of the position detection procedures for operating one of the proximity sensor systems. The method begins by checking whether a rotational tilt angle is greater than a first angle threshold and less than a second angle threshold (ie, -145 degrees and 145 degrees, respectively), and checking one or more The absolute value of the measured data on one of the axes is less than a first absolute value threshold (i.e., 600 mg). If the inquiry returns false, the location detection procedure returns false or no (N).

After this inquiry, the method can check if the system is in a near mode phase (i.e., the positional state is close). If the state is not close, the method checks if the absolute value of the measured data on one or more of the axes is less than a second absolute value threshold (i.e., 500 mg). If the state is close, another query is made as to whether the rotational tilt angle is greater than a third angle threshold (ie, -5 degrees) and less than a fourth angle threshold (ie, 5 degrees). And whether the rotational tilt angle is greater than a fifth angle threshold (ie, 85 degrees) and less than a sixth angle threshold (ie, 95 degrees), and one of the one or more axes is measured Whether one of the absolute values is greater than a third absolute value threshold (ie, 300 mg). If the query returns true, the location detection procedure returns true or (Y). Otherwise, the program returns false or no (N).

In an embodiment, the invention may include a method of operating a proximity sensor system. The previously described methods and sub-methods can be added together, interchanged, and reordered depending on the particular application. The previously described program flow contains only examples, depending on the application, which can be extended or reduced. Those skilled in the art will recognize variations, modifications, and alternatives.

It is also to be understood that the examples and embodiments set forth herein are for illustrative purposes only, and that various modifications and changes may be made by those skilled in the art and are intended to be included in the spirit and scope of the application and the accompanying application Within the scope of the patent scope.

Claims (20)

A method for proximity detection implemented on a portable device, the portable device being programmed to perform the method, the method comprising: determining, by means of a physical sensor of the portable device An initial perturbation data of one of the previous status data and the current status data; determining, by the physical sensor of the portable device, the tracking point data including one or more tracking data; the physical sense of the portable device And using the tracking point data to determine a stable position data; and determining, by the processor of the portable device, an action to be performed based on the initial disturbance data, the tracking point data, and the stable position data. The method of claim 1, further comprising: comparing, by the processor of the portable device, a difference between the previous state data and the current state data with one or more first thresholds; wherein the one or more Each of the first thresholds includes a ratio between a sensitivity parameter and a shake detection parameter. The method of claim 2, wherein the initial disturbance data comprises an X-axis disturbance data and a Z-axis disturbance data, and wherein the one or more first thresholds comprise: an X-axis first threshold, which includes the sensitivity parameter A ratio between an X-axis shake detection parameter and a Z-axis first threshold, which includes a ratio between the sensitivity parameter and a Z-axis shake detection parameter. The method of claim 1, wherein the determining of the tracking point data comprises: sampling two or more consecutive points in the (x, y, z) axis data; the method further comprising: by the portable device The processor compares the difference between the first point in the (x, y, z) axis data and the last point in the (x, y, z) axis data and one or more second thresholds a value; wherein each of the one or more second thresholds comprises a ratio between a sensitivity parameter and a movement parameter. The method of claim 4, wherein the one or more second thresholds comprise: an X-axis second threshold, including a ratio between the sensitivity parameter and an X-axis movement parameter, and a Z-axis A second threshold that includes a ratio between the sensitivity parameter and a Z-axis movement parameter. The method of claim 5, further comprising: comparing, by the processor of the portable device, the last point in the (x, y, z) data from the one or more tracking data with one or more third a threshold value and one or more fourth threshold values; wherein each of the one or more third threshold values includes a ratio between the sensitivity parameter and a position parameter; wherein the one or more Each of the fourth thresholds includes a sum of the sensitivity parameter and an offset value. The method of claim 6, wherein the one or more third thresholds comprise: an X-axis third threshold value including a ratio between the sensitivity parameter and an X-axis position parameter, a Y-axis a three-point limit value including a ratio between the sensitivity parameter and a Y-axis position parameter, and a Z-axis third threshold value including a sum of the sensitivity parameter and a Z-offset value and a Z-axis negative A ratio between positional parameters. The method of claim 6, wherein the one or more fourth thresholds comprise: an X-axis fourth threshold, comprising a sum of the sensitivity parameter and an X offset value, and a Y-axis fourth threshold a value comprising a sum of the sensitivity parameter and a Y offset value, and a Z-axis fourth threshold, including a sum of the sensitivity parameter and a Z offset value The ratio between a positive position parameter and a Z axis. The method of claim 1, wherein the determining of the action to be performed comprises: determining whether the initial perturbation data exceeds one or more first thresholds, and determining whether the tracking point data exceeds one or more second thresholds a value, and determining whether the stable location data exceeds one or more third and fourth thresholds. The method of claim 1, wherein the physical sensor comprises an accelerometer, a gyroscope sensor, a magnetic field sensor or a MEMS entity sensor. A portable device for determining a proximity of a user, comprising: a physical sensor configured to determine an initial perturbation data including one of a previous status data and a current status data, including one or more traces Tracking point data and using one of the tracking point data to stabilize location data; a processor coupled to the physical sensor, wherein the processor is programmed to base the tracking data based on the initial disturbance data And the stable position data to determine one of the actions to be performed. The device of claim 11, wherein the processor is programmed to compare a difference between the prior state data and the current state data with one or more first thresholds; wherein the one or more first thresholds Each of the values includes a ratio between a sensitivity parameter and a shake detection parameter. The device of claim 12, wherein the initial disturbance data comprises an X-axis disturbance data and a Z-axis disturbance data, and wherein the one or more first thresholds comprise: an X-axis first threshold, the sensitivity parameter A ratio between an X-axis shake detection parameter and a Z-axis first threshold, which includes a ratio between the sensitivity parameter and a Z-axis shake detection parameter. The device of claim 11, wherein the determination of the tracking point data comprises: sampling two or more consecutive points in the (x, y, z) axis data; wherein the processor is Stylizing to compare the difference between the first point in the (x, y, z) axis data and the last point in the (x, y, z) axis data and one or more second thresholds; Each of the plurality of second thresholds includes a ratio between a sensitivity parameter and a movement parameter. The apparatus of claim 14, wherein the one or more second thresholds comprise: an X-axis second threshold value including a ratio between the sensitivity parameter and an X-axis movement parameter, and a Z-axis A second threshold that includes a ratio between the sensitivity parameter and a Z-axis movement parameter. The device of claim 14, wherein the processor is programmed to compare the last point in the (x, y, z) data from the one or more tracking data with one or more third thresholds and one Or a plurality of fourth thresholds; wherein each of the one or more third thresholds includes a ratio between the sensitivity parameter and a position parameter; wherein the one or more fourth thresholds Each of these includes a sum of the sensitivity parameter and an offset value. The apparatus of claim 16, wherein the one or more third thresholds comprise: an X-axis third threshold value including a ratio between the sensitivity parameter and an X-axis position parameter, and a Y-axis a third threshold value including a ratio between the sensitivity parameter and a Y-axis position parameter, and a Z-axis third threshold value including a sum of the sensitivity parameter and a Z-offset value and a Z-axis One ratio between negative position parameters. The apparatus of claim 16, wherein the one or more fourth thresholds comprise: an X-axis fourth threshold, comprising a sum of the sensitivity parameter and an X offset value, and a Y-axis fourth threshold Value, which includes the total of the sensitivity parameter and a Y offset value And, and a Z-axis fourth threshold, which includes a ratio between the sum of the sensitivity parameter and a Z-offset value and a Z-axis positive position parameter. The device of claim 11, wherein the determining of the action to be performed comprises: determining whether the initial perturbation data exceeds one or more first thresholds, and determining whether the tracking point data exceeds one or more second thresholds a value, and determining whether the stable location data exceeds one or more third and fourth thresholds. The device of claim 11, wherein the physical sensor comprises an accelerometer, a gyroscope sensor, a magnetic field sensor or a MEMS entity sensor.