CN107817534B - Data acquisition method and device of intelligent wearable device and intelligent wearable device - Google Patents
Data acquisition method and device of intelligent wearable device and intelligent wearable device Download PDFInfo
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Abstract
The invention is suitable for the technical field of electronic communication, and provides a data acquisition method and a data acquisition device of intelligent wearable equipment and the intelligent wearable equipment, wherein the data acquisition method and the data acquisition device comprise the following steps: acquiring state information of a proximity sensor of the intelligent wearable device, and acquiring motion state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; the motion state data is used for representing a static or non-static state of the intelligent wearable device; determining the wearing state of the intelligent wearing equipment according to the motion state data; and executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment. On the basis of the approach information of the external object, the motion state information of the intelligent wearable device is combined, and the data of the intelligent wearable device when the user wears the intelligent wearable device is accurately collected.
Description
Technical Field
The invention belongs to the technical field of electronic communication, and particularly relates to a data acquisition method and device of intelligent wearable equipment and the intelligent wearable equipment.
Background
The intelligent wearable device enables a user to know the body, life and other conditions more clearly by collecting and processing physiological data of the user. In the using process of the intelligent wearable device, whether the user wears the device is detected, and after the intelligent wearable device is worn by the user, current user data are collected so as to correctly reflect results of health indexes, behavior habits, life preferences and the like of the user.
In the prior art, whether the intelligent wearable equipment is worn or not is detected through a capacitive sensor, and when an object shields a proximity sensor, the intelligent wearable equipment is judged to be worn; and when no object is shielded, determining that the clothes are not worn. When the intelligent wearable device is not worn and an object blocks the proximity sensor, the detection mode can be misjudged as a worn state, so that the user data acquired by the intelligent wearable device is wrong.
Disclosure of Invention
In view of this, embodiments of the present invention provide a data acquisition method and apparatus for an intelligent wearable device, and an intelligent wearable device, so as to solve the problem that in the detection manner in the prior art, when the intelligent wearable device is not worn and an object blocks a proximity sensor, the intelligent wearable device may be erroneously determined as a worn state, so that user data acquired by the intelligent wearable device is erroneous.
The first aspect of the embodiment of the invention provides a data acquisition method for intelligent wearable equipment, which comprises the following steps:
acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information comprises a proximity state or a distancing state;
if the state information of the proximity sensor is in a proximity state, acquiring motion state data of the intelligent wearable device; the motion state data is used for representing a static or non-static state of the intelligent wearable device;
determining the wearing state of the intelligent wearing equipment according to the motion state data;
and executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
The state information of the proximity sensor of the intelligent wearable device is obtained, and the state information comprises:
detecting whether the proximity sensor generates an interrupt signal;
if an interrupt signal generated by the proximity sensor is detected, acquiring a proximity value detected by the proximity sensor;
if the approach value is smaller than the approach value threshold value, the approach sensor is in an approach state currently; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
The intelligent wearable device further comprises an acceleration sensor, and if the state information of the proximity sensor is in a proximity state, the motion state data of the intelligent wearable device is acquired, and the method specifically comprises the following steps:
acquiring acceleration data acquired by the acceleration sensor; extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state;
calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data;
and if the matching degree between the target acceleration characteristic data and the acceleration characteristic data is greater than or equal to a preset matching degree threshold value, judging that the intelligent wearable equipment is in a static state.
The determining the wearing state of the intelligent wearable device according to the motion state data specifically includes:
if the motion state data represent that the intelligent wearable device is in a static state, judging whether the time for the intelligent wearable device to keep the static state exceeds a preset time threshold value;
if yes, determining that the intelligent wearable device is in an unworn state;
the determining the wearing state of the intelligent wearable device according to the motion state data further comprises:
and if the motion state data represent that the intelligent wearable device is in a non-static state, determining that the intelligent wearable device is in a wearable state.
A second aspect of the embodiments of the present invention provides a data acquisition device for an intelligent wearable device, including:
the state acquisition unit is used for acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information comprises a proximity state or a distancing state;
the data acquisition unit is used for acquiring motion state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; wherein the motion state data is used to characterize a static or non-static state of the smart wearable device;
the state determining unit is used for determining the wearing state of the intelligent wearing equipment according to the motion state data;
and the data acquisition unit is used for executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
Wherein the state acquiring unit includes:
a signal detection subunit for detecting whether the proximity sensor generates an interrupt signal;
a proximity value acquisition subunit, configured to acquire a proximity value detected by the proximity sensor if an interrupt signal generated by the proximity sensor is detected;
the proximity state determining subunit is used for determining that the proximity sensor is currently in a proximity state if the proximity value is smaller than the proximity value threshold; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
The state determination unit includes:
the characteristic extraction subunit is used for acquiring acceleration data acquired by the acceleration sensor; extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state;
the matching degree calculation operator unit is used for calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data;
and the state judgment subunit is used for judging that the wearable equipment only is in a static state if the matching degree between the target acceleration characteristic data and the acceleration data is greater than or equal to a preset matching degree threshold value.
The state determination unit further includes:
the state keeping judging subunit is configured to judge whether the time for the intelligent wearable device to keep the stationary state exceeds a preset time threshold if the motion state data represents that the intelligent wearable device is in the stationary state;
and the non-wearing state determining subunit is used for determining that the intelligent wearing equipment is in a non-wearing state if the non-wearing state is exceeded.
The state determination unit further includes:
and the wearing state determining subunit is configured to determine that the intelligent wearable device is in a wearing state if the motion state data represents that the intelligent wearable device is in a non-static state.
A third aspect of an embodiment of the present invention provides an intelligent wearable device, including: the device comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are connected with each other, the memory is used for storing a computer program for supporting an apparatus to execute the method, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the method of the first aspect.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium having stored thereon a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of the first aspect described above.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: through combining the approaching information of the external object with the internal moving information, the state of the intelligent wearable device is more accurately detected, and the purpose of acquiring accurate data is achieved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of a data acquisition method of an intelligent wearable device according to an embodiment of the present invention;
fig. 2 is a flowchart of a data acquisition method of an intelligent wearable device according to another embodiment of the present invention;
fig. 3 is a schematic diagram of a data acquisition device of an intelligent wearable device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a data acquisition device of an intelligent wearable device according to another embodiment of the present invention;
fig. 5 is a schematic diagram of an intelligent wearable device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
Referring to fig. 1, fig. 1 is a flowchart of a data acquisition method of an intelligent wearable device according to an embodiment of the present invention. The execution main part of intelligent wearing equipment's data acquisition is intelligent wearing equipment in this embodiment, and intelligent wearing equipment can be equipment such as intelligent wrist-watch, intelligent bracelet, intelligent glasses or intelligent sports shoes, does not do the restriction here. The data acquisition method of the intelligent wearable device shown in fig. 1 may include the following steps:
s101: acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information includes a close state or a far state.
In this embodiment, a device capable of sensing the proximity of an object, for example, a proximity sensor, is installed in the smart wearable device, and the proximity of the object is recognized by the proximity sensor having a sensitivity characteristic to the approaching object, and a corresponding signal is output. The proximity sensor can be used to replace a contact detection sensor device, which can detect information such as the distance or position between an object to be detected and an external object without contacting the object to be detected.
In this embodiment, the current state information of the intelligent wearable device is collected through the proximity sensor. The state information includes a close state or a far state. When an object approaches the intelligent wearable device or the intelligent wearable device approaches an external object, the state information reported by the proximity sensor is proximity state information. When an object is far away from the intelligent wearable device, or when the intelligent wearable device is far away from an external object, the state information reported by the proximity sensor is far away state information.
Further, when the state information is the proximity state information, the proximity sensor may be shielded by an external object, and the state information of the proximity sensor is still the proximity state information, especially when the intelligent wearable device is not in the wearable state. Therefore, under similar conditions, the state of the intelligent wearable device is detected only by one detection device of the proximity sensor, so that misjudgment can be caused, and under the wrong state of the intelligent wearable device, the problem that the use data collected later do not correspond to the use data can be caused.
The state information of the proximity sensor of the intelligent wearable device is obtained to determine whether the current state of the intelligent wearable device and the external object is close to or far away from, and further determine whether the external object is close to the intelligent wearable device.
S102: if the state information of the proximity sensor is in a proximity state, acquiring motion state data of the intelligent wearable device; the motion state data is used for representing a static or non-static state of the intelligent wearable device.
When the proximity sensor is in a proximity state, it indicates that an object other than the proximity sensor exists around the smart wearable device, and the external object may be an object such as a user, a desk, or a clothes hanger, which is not limited herein. For example, the user wears the smart wearable device on the body, and the smart wearable device is placed on a desk or hung on a clothes rack, and in these cases, the proximity sensor is in a proximity state.
In the use process of the intelligent wearable device, the intelligent wearable device can move all the time as being worn on a human body, so that motion data is generated, and the intelligent wearable device is in a non-static state; but also may be stationary due to being placed on or hung from an object, in this case a stationary state. Therefore, the state data of the intelligent wearable device is collected to represent the motion state of the intelligent wearable device, wherein the motion state comprises a static state and a non-static state.
For example, the motion state data of the smart wearable device may be collected by an acceleration sensor. Preferably, the motion state data of the intelligent wearable device are acquired through a three-axis acceleration sensor. The triaxial acceleration sensor works based on the basic principle of acceleration. The acceleration is a space vector, and on one hand, components on three coordinate axes of the intelligent wearable device need to be measured to accurately know the motion state of the intelligent wearable device; on the other hand, on the occasion that intelligent wearing equipment moving direction is not known in advance, detect acceleration signal through triaxial acceleration sensor. Because the triaxial acceleration sensor is also based on the gravity principle, the inclination angle of a double shaft of plus or minus 90 degrees or a double shaft of 0-360 degrees can be realized by using the triaxial acceleration sensor, and the later-stage precision is higher than that of the double-shaft acceleration sensor by being more than 60 degrees in the measurement angle through correction. The three-axis acceleration sensor has the characteristics of small volume and light weight, can measure the spatial acceleration, and can comprehensively and accurately reflect the motion property of the intelligent wearable device.
Further, when acquiring the state data of the intelligent wearable device, the state of the intelligent wearable device may be maintained for a certain time, and therefore, the state data of the intelligent wearable device within a certain time period needs to be acquired, so as to acquire the motion condition of the device within the time period more comprehensively and accurately.
The state data of the intelligent wearable device are obtained to determine the motion state of the intelligent wearable device under the condition that an object is close, and further, under the condition that the state information of the intelligent wearable device is determined, whether the intelligent wearable device is in a wearing state or a non-wearing state is accurately determined through the motion state of the intelligent wearable device.
S103: and determining the wearing state of the intelligent wearing equipment according to the motion state data.
The state data of the intelligent wearable device is the motion data of the intelligent wearable device in a certain period of time, and the state data can be the data of the intelligent wearable device such as the acceleration value, the positioning information, the moving speed and the average speed, and is not limited here.
Optionally, by acquiring the positioning information of the intelligent wearable device at different times, and comparing the acquired positioning information, if the positioning information of the intelligent wearable device at the first time is different from the positioning information of the intelligent wearable device at the second time, it is indicated that the intelligent wearable device has moved between the two times, that is, the intelligent wearable device is in a non-stationary state in the time period; if the corresponding positioning information at two moments is the same, the intelligent wearable device is in a static state.
Preferably, when the acquired state data of the intelligent wearable device is an acceleration value, if the acceleration value is greater than zero, the intelligent wearable device is in a non-static state, and if the acceleration value is equal to zero, the intelligent wearable device is in a static state.
Further, when comparing the acquired state data of the intelligent wearable device with the pre-stored feature data corresponding to the non-worn state, the state of the intelligent wearable device may be maintained for a certain time, and therefore, the state data of the intelligent wearable device in the time period needs to be compared with the pre-stored feature data corresponding to the non-worn state, so as to more comprehensively determine the motion condition of the device in the time period.
And if the motion state is a static state, judging that the intelligent wearable device is in a non-wearing state.
If the acquired state data of the intelligent wearable device is the same as the pre-stored characteristic data corresponding to the non-wearable state, or the matching degree of the two types of data within a certain time period is greater than or equal to a preset matching degree threshold value, judging that the intelligent wearable device is in a static state; and if the motion state is a non-static state, judging that the intelligent wearable device is in a wearable state.
S104: and executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
When the intelligent wearable device is in a wearing state, various data of a user are collected; and if the wearable device is in the unworn state, stopping collecting various data.
According to the scheme, whether the intelligent wearable device is in the proximity state or not is determined by acquiring the state information of the proximity sensor of the intelligent wearable device; and then acquiring the state data of the intelligent wearable device, determining the wearing state of the intelligent wearable device according to the state data, and finally executing corresponding data acquisition actions according to the wearing state of the intelligent wearable device. On the basis of the approach information of an external object, the motion state information of the intelligent wearable device is combined, and the use data and the user information of the intelligent wearable device when being worn are collected more accurately and in real time.
Referring to fig. 2, fig. 2 is a flowchart of a data acquisition method of an intelligent wearable device according to another embodiment of the present invention. The execution main part of data acquisition of intelligent wearing equipment in this embodiment can be intelligent wearing equipment such as intelligent wrist-watch, intelligent bracelet, intelligent glasses or intelligent sports shoes, does not do the restriction here. The data acquisition method of the intelligent wearable device as shown in fig. 2 may include the following steps:
s201: acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information includes a close state or a far state.
Step S201 includes steps S2011-S2013.
S2011: detecting whether the proximity sensor generates an interrupt signal.
The proximity sensor detects whether an external object approaches the vicinity of a detection object in a non-contact manner. In the present embodiment, the proximity sensor may be of an inductive type, a capacitive type, an ultrasonic type, a photoelectric type, a magnetic type, or the like, and is not limited thereto, and the proximity sensor may be a proximity switch that uses a direct-current magnetic field generated by a magnetic force, such as an inductive type proximity sensor that detects the presence of a metal, a capacitive type proximity sensor that detects the presence of a metal or a non-metal object, or the like.
When an external object approaches or leaves the intelligent wearable device, the external magnetic field of the proximity sensor in the intelligent wearable device can be influenced, eddy current generated on the surface of a conductor of the proximity sensor can cause magnetic loss, and an alternating-current magnetic field can be generated in a coil; the metal body of the proximity sensor generates eddy current, and the impedance changes, thereby generating an interrupt signal. Thus, the interrupt signal includes a close signal and a far signal.
Whether the proximity sensor generates the interrupt signal is determined by detecting a magnetic loss caused by an eddy current generated on a conductor surface of the proximity sensor and an alternating magnetic field generated in the coil, and detecting an impedance change caused by an eddy current generated in a metal body of the proximity sensor. Whether an external object is close to the intelligent wearable device or not is judged, and then the approaching conditions such as the distance between the object and the intelligent wearable device are accurately determined.
S2012: and if the interrupt signal generated by the proximity sensor is detected, acquiring a proximity value detected by the proximity sensor.
When the proximity sensor senses that an external object is close and generates an interrupt signal, a detected proximity value of the interrupt signal is acquired.
For example, the proximity value may be a distance between the external object and the smart wearable device. The laser emitted by the proximity sensor is reflected by an external object and then received by the proximity sensor, and the round-trip time of the laser is recorded. Half of the product of the light speed and the round trip time is the distance between the intelligent wearable device and the external object.
Illustratively, the proximity value may also be close to the magnitude of the impedance change caused by eddy currents generated by the metal body of the sensor.
Further, if the interrupt signal generated by the proximity sensor is not detected, state data of the intelligent wearable device is acquired; the state data is data used for representing the motion state of the intelligent wearable device, and the motion state comprises a static state and a non-static state. Determining the motion state of the intelligent wearable device according to the state data; if the motion state of the intelligent wearable device is a static state, the intelligent wearable device is judged to be in a non-wearing state.
And determining the distance between the external object and the intelligent wearable device by acquiring the approach value of the interrupt signal sent by the state information of the approach sensor of the intelligent wearable device so as to determine whether the external object and the intelligent wearable device are in the approach state.
S2013: if the approach value is smaller than the approach value threshold value, the approach sensor is in an approach state currently; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
The approach value threshold is stored in the smart wearable device in advance, and by comparing the approach value of the detected interrupt signal with the approach value threshold, when the approach value is within the approach value threshold range, the approach sensor is currently in an approach state.
Further, the interrupt signal generated by the proximity sensor includes a proximity signal and a distance signal, and therefore, a proximity threshold value and a distance threshold value for determining the type of the interrupt signal are previously stored in the proximity sensor. Meanwhile, when the parameters of the proximity sensor are configured in advance, the following parameters are also required to be configured: pulse frequency modulation, LED current, number of pulses per emission, emission interval, approach threshold, and departure threshold.
Illustratively, the pulse frequency modulation frequency of the proximity sensor is 60 kHz; the current value of the light emitting diode is 100 mA; the number of pulses transmitted each time is 12; the emission interval is 100 ms; the approach threshold is 80 and the departure threshold is 30.
Optionally, setting an approach threshold to be 80 and a departure threshold to be 30, and if an approach value of the currently acquired interrupt signal is greater than or equal to 80, the interrupt signal is an approach signal; if the approach value of the currently acquired interrupt signal is less than 30, the interrupt signal is a far signal.
Optionally, the approach threshold and the departure threshold are both set to be 60, and if the approach value of the currently acquired interrupt signal is greater than or equal to 60, the interrupt signal is an approach signal; if the approach value of the currently acquired interrupt signal is less than 60, the interrupt signal is a far signal.
It is understood that the user sets the magnitudes of the approach value threshold and the distance value threshold by using the requirement or the environmental requirement, and the magnitudes of the approach value threshold and the distance value threshold may be the same or different, and are not limited herein.
The intelligent wearable device firmware program judges whether the intelligent wearable device is in an approaching or leaving state through generating an approaching or leaving interrupt signal by the approach sensor. If the intelligent wearable device is in the close state, the intelligent wearable device is judged to be in the worn state currently.
S202: if the state information of the proximity sensor is in a proximity state, acquiring motion state data of the intelligent wearable device; the motion state data is used for representing a static or non-static state of the intelligent wearable device.
And if the state information of the proximity sensor is in a proximity state, acquiring the state data of the intelligent wearable device. In this scheme, intelligent wearing equipment is in two kinds of states, static state and non-static state. If it is detected that an external object approaches or blocks the intelligent wearable device, it cannot be determined that the intelligent wearable device is worn on the external object.
For example, when the smart wearable device is not worn, but the proximity sensor is accidentally blocked by an object, it is determined that the smart wearable device is worn according to the judgment method in the prior art, so that a misjudgment situation is generated. Therefore, the motion condition of the current intelligent wearable device needs to be determined through the state data of the intelligent wearable device.
When the intelligent wearable device is worn on a human body, the intelligent wearable device can generate a proximity signal and a movement signal. The motion state of the intelligent wearable device is detected through the motion state sensor, and then whether the intelligent wearable device moves or not is judged. Therefore, on the basis of the approaching information of the external object, whether the intelligent wearable device is in a wearable state or not is accurately detected by combining the motion state information of the intelligent wearable device.
S203: and if the state information of the proximity sensor is in a proximity state, acquiring the motion state data of the intelligent wearable device.
Step S203 specifically includes steps S2031 to S2033.
S2031: acquiring acceleration data acquired by the acceleration sensor; and extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state.
The method comprises the steps of obtaining state data of the intelligent wearable device, and extracting target feature data from the state data according to pre-stored feature data corresponding to the non-wearable state.
Illustratively, state data of the intelligent wearable device are sensed and collected through a three-axis acceleration sensor, the collected data are accelerations of the intelligent wearable device on three-dimensional space coordinate systems x, y and z, and the collection mode is as follows:
calculating a composite acceleration according to the accelerations of the x, y and z axes in a first time period, and extracting data related to prestored unworn state data as a first characteristic;
in a second time period, combining all the first features extracted in the first time period to form second features; the length of the second time period is greater than that of the first time period;
in a third time period, combining all the second features extracted in the second time period to form third features; the length of the third time period is greater than the length of the second time period.
Furthermore, a histogram is formed according to the counted data features, and the distribution condition of the motion data features of the intelligent wearable device is represented by a series of longitudinal stripes or line segments with different heights, so that the motion condition of the intelligent wearable device is displayed by a more obvious and intuitive data image.
It should be noted that, in the process of extracting the target feature data, the time period for extraction and the number of statistics may be obtained by presetting, and this is not limited here. Illustratively, data related to the pre-stored unworn state data is extracted as a first feature every 2 seconds, and the histogram feature distribution rule of the previous time is counted every 1 minute and every 30 minutes thereafter, respectively.
Through the mode, the data characteristics in the short time are extracted at the previous time, the data characteristics at the previous time are counted in a later longer time period, the motion data of the intelligent wearable device are collected in real time, the distribution rule with the motion data can be integrally obtained, and the motion state of the intelligent wearable device is obtained from the motion data more accurately and macroscopically.
S2032: and calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data.
The pre-stored characteristic data corresponding to the non-wearing state is the motion data of the intelligent wearing device in the non-wearing state, and the target characteristic data is the data related to the pre-stored characteristic data corresponding to the non-wearing state and the collected state data.
Because intelligent wearing equipment is easily influenced by factors such as external environment, user behavior or physiological conditions, under many circumstances, the motion data that the sensor was gathered all have certain instability, can not compare through accurate motion data and the corresponding characteristic data of the not wearing state of prestoring, otherwise, can filter a lot of valuable information. Therefore, in the present scheme, after the target feature data is acquired, the time relationship between the currently acquired motion data and the feature data is determined by calculating the matching degree between the target feature data and the feature data.
It should be noted that the target feature data and the feature data are not required to be all the same. The matching degree between the target characteristic data and the characteristic data is calculated, and the matching degree is controlled to exceed a certain range.
For example, in a certain period of time, the total data amount of the data feature is a, and the data difference amount between the target feature data and the feature data is D, then the ratio between the total data amount of the target feature data and the data difference amount may be used as the matching degree between the target feature data and the feature data.
The difference relation between the real-time motion data of the intelligent wearable device and the standard target characteristic data within a certain period of time is determined by calculating the matching degree between the target characteristic data and the characteristic data, and then the motion state of the intelligent wearable device is determined through the matching degree.
S2033: and if the matching degree between the target acceleration characteristic data and the acceleration characteristic data is greater than or equal to a preset matching degree threshold value, judging that the intelligent wearable equipment is in a static state.
And the preset matching degree threshold value is used for evaluating the matching degree between the calculated target characteristic data and the characteristic data, so that the motion state of the intelligent wearable equipment is determined.
Illustratively, the threshold value of the matching degree of the static state is set to be 0.7, and when the matching degree D/a between the target characteristic data and the target characteristic data is greater than or equal to 0.7, it indicates that the characteristic data and the target characteristic data have a higher matching degree, and the motion state of the intelligent wearable device corresponding to the characteristic data conforms to the motion state corresponding to the target characteristic data. Therefore, the motion state of the wearable device within the period of time corresponding to the characteristic data is a static state.
Alternatively, the threshold of the degree of matching between the static state and the non-static state may be two values. For example, the threshold value of the degree of matching in the non-stationary state is 0.2, and the threshold value of the degree of matching in the stationary state is 0.7. When the matching degree between the target characteristic data and the characteristic data is greater than or equal to 0.7, the motion state of the wearable equipment in the period of time is a static state; when the matching degree between the target characteristic data and the characteristic data is less than or equal to 0.3, the motion state of the wearable device in the period of time is a non-static state.
Alternatively, the threshold of the degree of matching between the static state and the non-static state may be the same value. For example, the threshold value of the matching degree between the static state and the non-static state is 0.8, and when the matching degree between the target feature data and the feature data is greater than or equal to 0.8, the motion state of the wearable device within the period of time is the static state; when the matching degree between the target characteristic data and the characteristic data is less than 0.8, the motion state of the wearable device in the period of time is a non-static state.
It can be understood that, the user sets the size of the threshold of the degree of matching between the static state and the non-static state by using the requirement or the environmental requirement, and the threshold of the degree of matching between the static state and the non-static state may be the same or different, and is not limited herein.
Through the motion state data of gathering intelligent wearing equipment to confirm intelligent wearing equipment's motion state, revised the misjudgment that only judges intelligent wearing equipment's motion state and cause with the sensor, laid good basis for the practical application of accurate collection intelligent wearing equipment data and intelligent wearing equipment.
And if the motion state is a static state, judging that the intelligent wearable device is in a non-wearing state. After the motion state of the wearable device within the period of time corresponding to the collected characteristic data is determined to be a static state, and under the condition that the proximity sensor of the intelligent wearable device determines that the proximity signal is generated, the intelligent wearable device is determined to be in an unworn state.
And if the motion state is a non-static state, judging that the intelligent wearable equipment is in a wearing state.
After the motion state of the wearable device within the period of time corresponding to the collected characteristic data is determined to be a non-static state, and under the condition that the proximity sensor of the intelligent wearable device determines that a proximity signal is generated, the intelligent wearable device is determined to be in a wearable state.
S204: and executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
When the intelligent wearable device is in a wearing state, acquiring various data of a user to determine a physiological state of the user when the intelligent wearable device is worn; if the wearable intelligent wearable device is not in the wearable state, the wearable intelligent device stops collecting various data, the wearable intelligent device enters the standby state, the electric quantity consumption of continuous data collection is avoided being too large, the cruising ability of the wearable intelligent device is improved, and the accuracy of data collection is improved.
According to the scheme, whether the proximity sensor generates the interrupt signal or not is detected, the current state of the proximity sensor is determined according to the proximity value detected by the proximity sensor and the preset proximity value threshold, and if the state information of the proximity sensor is in the proximity state, the state data of the intelligent wearable device is acquired. Extracting target characteristic data from the state data according to the characteristic data corresponding to the pre-stored non-wearing state, judging the motion state of the intelligent wearing equipment by calculating the matching degree between the two types of data and comparing the matching degree with a preset matching degree threshold value, judging that the intelligent wearing equipment is in the non-wearing state if the intelligent wearing equipment is in the static state, and executing corresponding data acquisition action if the intelligent wearing equipment is in the wearing state otherwise. On the basis of the approach information of an external object, the motion state information of the intelligent wearable device is combined, the one-sidedness of data acquisition of the intelligent wearable device only through one sensor is corrected, the possibility of misjudgment is reduced, and the data information of the intelligent wearable device is acquired more accurately and in real time.
Referring to fig. 3, fig. 3 is a schematic view of a data acquisition device of an intelligent wearable device according to an embodiment of the present invention. The apparatus 300 may be a smart watch, a smart bracelet, smart glasses, or a smart sports shoe, which is not limited herein. The apparatus 300 of the present embodiment includes units for performing the steps in the embodiment corresponding to fig. 1, and please refer to fig. 1 and the related description in the embodiment corresponding to fig. 1 for details, which are not repeated herein. The device 300 of the present embodiment includes a state acquisition unit 301, a data acquisition unit 302, a state determination unit 303, and a data acquisition unit 304.
The state acquiring unit 301 is configured to acquire state information of a proximity sensor of the smart wearable device; wherein the state information includes a close state or a far state.
The data acquisition unit 302 is configured to acquire motion state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; the motion state data is used for representing a static or non-static state of the intelligent wearable device.
The state determining unit 303 is configured to determine a wearing state of the smart wearable device according to the motion state data.
The data acquisition unit 304 is configured to execute a corresponding data acquisition action according to the wearing state of the intelligent wearable device.
According to the scheme, whether the intelligent wearable device is in the proximity state or not is determined by acquiring the state information of the proximity sensor of the intelligent wearable device; and then acquiring the state data of the intelligent wearable device, determining the motion state of the intelligent wearable device according to the state data, and finally executing corresponding data acquisition actions according to the wearing state of the intelligent wearable device. On the basis of the approach information of the external object, the motion state information of the intelligent wearable device is combined, and the data of the intelligent wearable device in the use process is collected more accurately and in real time.
Referring to fig. 4, fig. 4 is a schematic view of a data acquisition device of an intelligent wearable device according to an embodiment of the present invention. The apparatus 400 may be a smart watch, a smart bracelet, smart glasses, or a smart sports shoe, which is not limited herein. The apparatus 400 of the present embodiment includes units for performing the steps in the embodiment corresponding to fig. 2, please refer to fig. 2 and the related description in the embodiment corresponding to fig. 2, which are not repeated herein. The apparatus 400 of this embodiment includes a state obtaining unit 401, a data obtaining unit 402, a state determining unit 403, and a data acquiring unit 404, further, the state obtaining unit 401 further includes a signal detecting sub-unit 4011, a proximity value obtaining sub-unit 4012, and a proximity state determining sub-unit 4013, and the state determining unit 403 further includes a feature extracting sub-unit 4031, a matching degree sub-unit 4032, and a state determining sub-unit 4033.
The state obtaining unit 401 is configured to obtain state information of a proximity sensor of the smart wearable device; wherein the state information includes a close state or a far state.
Further, the state acquisition unit 401 further includes a signal detection sub-unit 4011, a proximity value acquisition sub-unit 4012, and a proximity state determination sub-unit 4013.
The signal detecting sub-unit 4011 is configured to detect whether the proximity sensor generates an interrupt signal.
The proximity value acquiring sub-unit 4012 is configured to acquire a proximity value detected by the proximity sensor if the interrupt signal generated by the proximity sensor is detected.
The approach state determination sub-unit 4013 is configured to determine that the approach sensor is currently in an approach state if the approach value is smaller than the approach value threshold; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
The data acquisition unit 402 is configured to acquire state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; the motion state data is used for representing a static or non-static state of the intelligent wearable device.
The state determining unit 403 is configured to determine a wearing state of the smart wearable device according to the motion state data.
Further, the state determination unit 403 further includes a feature extraction subunit 4031, a matching degree operator unit 4032, and a state determination subunit 4033.
A feature extraction subunit 4031, configured to acquire acceleration data acquired by the acceleration sensor; and extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state.
And the matching degree operator unit 4032 is used for calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data.
A state determining subunit 4033, configured to determine that the intelligent wearable device is in a stationary state if a matching degree between the target acceleration characteristic data and the acceleration characteristic data is greater than or equal to a preset matching degree threshold.
And the data acquisition unit 404 is configured to execute a corresponding data acquisition action according to the wearing state of the intelligent wearable device.
According to the scheme, whether the proximity sensor generates the interrupt signal or not is detected, the current state of the proximity sensor is determined according to the proximity value detected by the proximity sensor and the preset proximity value threshold, and if the state information of the proximity sensor is in the proximity state, the state data of the intelligent wearable device is acquired. Extracting target characteristic data from the state data according to characteristic data corresponding to a pre-stored non-wearing state, judging the motion state of the intelligent wearing equipment by calculating the matching degree between the two types of data and comparing the matching degree with a preset matching degree threshold value, judging that the intelligent wearing equipment is in the non-wearing state if the intelligent wearing equipment is in a static state, otherwise, judging that the intelligent wearing equipment is in the wearing state, and executing corresponding data acquisition action according to the wearing state of the intelligent wearing equipment. On the basis of the approach information of an external object, the motion state information of the intelligent wearable device is combined, the one-sidedness of data acquisition of the intelligent wearable device only through one sensor is corrected, the possibility of misjudgment is reduced, and the data information of the intelligent wearable device is acquired more accurately and in real time.
Referring to fig. 5, fig. 5 is a schematic view of an intelligent wearable device according to an embodiment of the present invention. The smart wearable device 500 in the present embodiment as shown in fig. 5 may include: a processor 501, a memory 502 and a computer program 503 stored in the memory 502 and executable on the processor 501, such as a program that calculates a degree of match between the target acceleration characteristic data and the acceleration characteristic data. The processor 501 executes the computer program 503 to implement the steps in the above-mentioned data acquisition method embodiments of the intelligent wearable device. Such as S101 to S104 shown in fig. 1. Alternatively, the processor 501, when executing the computer program 503, implements the functions of the units in the above-described device embodiments, such as the units 301 to 304 described in fig. 3.
Illustratively, the computer program 503 may be divided into one or more units, which are stored in the memory 502 and executed by the processor 501 to accomplish the present invention. The one or more units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used for describing the execution process of the computer program 503 in the smart wearable device 500. For example, the computer program 503 may be divided into a signal detection subunit, a proximity value acquisition subunit, a proximity state determination subunit, a state acquisition unit, a data acquisition unit, a state determination unit, and a data acquisition unit, and each unit has the following specific functions:
the state acquisition unit is used for acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information includes a close state or a far state.
Further, the state acquiring unit further includes a signal detecting subunit, a proximity value acquiring subunit, and a proximity state determining subunit, specifically:
the signal detection subunit is used for detecting whether the proximity sensor generates an interrupt signal.
The approach value acquisition subunit is used for acquiring an approach value detected by the approach sensor if the interrupt signal generated by the approach sensor is detected.
The proximity state determination subunit is used for determining that the proximity sensor is currently in a proximity state if the proximity value is smaller than the proximity value threshold; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
The data acquisition unit is used for acquiring motion state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; wherein the motion state data is used to characterize a static or non-static state of the smart wearable device.
The state determining unit is used for determining the wearing state of the intelligent wearing equipment according to the motion state data.
And the data acquisition unit is used for executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
Further, the state determination unit further includes a feature extraction subunit, a matching degree subunit, and a state judgment subunit, specifically:
the characteristic extraction subunit is used for acquiring acceleration data acquired by the acceleration sensor; and extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state.
And the matching degree operator unit is used for calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data.
The state judgment subunit is configured to judge that the intelligent wearable device is in the stationary state if the matching degree between the target feature data and the feature data is greater than or equal to a preset matching degree threshold value.
And the data acquisition unit is used for executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
The smart wearable device 500 may be a smart watch, a smart bracelet, smart glasses, or a smart sports shoe, and is not limited herein. A processor 501 and a memory 502. Those skilled in the art will appreciate that fig. 5 is only an example of the smart wearable device 500, and does not constitute a limitation to the smart wearable device 500, and may include more or less components than those shown, or combine some components, or different components, for example, the means for adjusting the closed working environment may further include an input/output device, a network access device, a bus, etc.
The Processor 501 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 502 may be an internal storage unit of the smart wearable device 500, such as a hard disk or a memory of the smart wearable device 500. The memory 502 may also be an external storage device of the Smart wearable device 500, such as a plug-in hard disk provided on the Smart wearable device 500, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 502 may also include both an internal storage unit and an external storage device of the smart wearable device 500. The memory 502 is used for storing the computer programs and other programs and data required by the means for regulating the closed work environment. The memory 502 may also be used to temporarily store data that has been output or is to be output.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same. Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (8)
1. A data acquisition method of intelligent wearable equipment is characterized by comprising the following steps:
acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information comprises a proximity state or a distancing state;
if the state information of the proximity sensor is in a proximity state, acquiring motion state data of the intelligent wearable device; the motion state data is used for representing a static or non-static state of the intelligent wearable device; the motion state data comprises acceleration data;
extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state, and making a histogram according to the target acceleration characteristic data; the histogram is used for displaying the motion condition of the intelligent wearable device;
calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data; the matching degree is the ratio of the total amount of the target acceleration characteristic data to the difference amount of the data; the data difference amount is a difference between the target acceleration characteristic data and the acceleration characteristic data;
if the matching degree between the target acceleration characteristic data and the acceleration characteristic data is greater than or equal to a preset matching degree threshold value, judging that the intelligent wearable device is in a static state;
determining the wearing state of the intelligent wearing equipment according to the motion state data;
and executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
2. The method of claim 1, wherein the obtaining the state information of the proximity sensor of the smart wearable device comprises:
detecting whether the proximity sensor generates an interrupt signal;
if an interrupt signal generated by the proximity sensor is detected, acquiring a proximity value detected by the proximity sensor;
if the approach value is smaller than the approach value threshold value, the approach sensor is in an approach state currently; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
3. The method according to claim 1 or 2, wherein the determining the wearing state of the smart wearable device according to the motion state data specifically includes:
if the motion state data represent that the intelligent wearable device is in a static state, judging whether the time for the intelligent wearable device to keep the static state exceeds a preset time threshold value;
and if so, determining that the intelligent wearable device is in an unworn state.
4. The method of claim 1, wherein the determining the wearing state of the smart wearable device from the motion state data further comprises:
and if the motion state data represent that the intelligent wearable device is in a non-static state, determining that the intelligent wearable device is in a wearable state.
5. The utility model provides an intelligence wearing equipment's data acquisition device which characterized in that includes:
the state acquisition unit is used for acquiring state information of a proximity sensor of the intelligent wearable device; wherein the state information comprises a proximity state or a distancing state;
the data acquisition unit is used for acquiring motion state data of the intelligent wearable device if the state information of the proximity sensor is in a proximity state; wherein the motion state data is used to characterize a static or non-static state of the smart wearable device; the motion state data comprises acceleration data;
the characteristic extraction subunit is used for extracting target acceleration characteristic data from the acceleration data according to acceleration characteristic data corresponding to a pre-stored non-wearing state and making a histogram according to the target acceleration characteristic data; the histogram is used for displaying the motion condition of the intelligent wearable device;
the matching degree calculation operator unit is used for calculating the matching degree between the target acceleration characteristic data and the acceleration characteristic data; the matching degree is the ratio of the total amount of the target acceleration characteristic data to the difference amount of the data; the data difference amount is a difference between the target acceleration characteristic data and the acceleration characteristic data;
the state judgment subunit is configured to judge that the intelligent wearable device is in a stationary state if the matching degree between the target acceleration characteristic data and the acceleration data is greater than or equal to a preset matching degree threshold;
the state determining unit is used for determining the wearing state of the intelligent wearing equipment according to the motion state data;
and the data acquisition unit is used for executing corresponding data acquisition actions according to the wearing state of the intelligent wearing equipment.
6. The data acquisition device of intelligent wearable equipment as claimed in claim 5, wherein the state acquisition unit comprises:
a signal detection subunit for detecting whether the proximity sensor generates an interrupt signal;
a proximity value acquisition subunit, configured to acquire a proximity value detected by the proximity sensor if an interrupt signal generated by the proximity sensor is detected;
the proximity state determining subunit is used for determining that the proximity sensor is currently in a proximity state if the proximity value is smaller than the proximity value threshold; and if the approach value is greater than or equal to the approach value threshold value, the approach sensor is in a far state currently.
7. An intelligent wearable device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the method of any of claims 1 to 4.
8. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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| CN109542215B (en) * | 2018-10-09 | 2022-03-08 | 中国矿业大学 | Wearing monitoring method for safety helmet |
| CN111239846B (en) * | 2020-02-12 | 2022-09-13 | 北京中科汇成科技有限公司 | Disposable sock automatic identification device |
| CN113534500B (en) * | 2020-04-14 | 2023-01-13 | 所乐思(深圳)科技有限公司 | Intelligent glasses, method for monitoring human body posture, medium, terminal and system |
| CN113805512B (en) * | 2021-09-16 | 2023-08-15 | 上海擎朗智能科技有限公司 | Control method and device of wearable device and storage medium |
| CN114366062B (en) * | 2022-03-18 | 2023-10-27 | 北京荣耀终端有限公司 | Wearable device, wearing detection method and medium thereof |
| CN116774597A (en) * | 2023-05-05 | 2023-09-19 | 杭州手趣科技有限公司 | Intelligent household equipment control method and system based on wearable equipment |
| CN116570251B (en) * | 2023-07-14 | 2023-10-03 | 北京中科心研科技有限公司 | Wearing equipment wearing judging method and device based on PPG (program G) signals |
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