CN113080944B - Bioelectric signal and spinal activity detection method, device and system - Google Patents
Bioelectric signal and spinal activity detection method, device and system Download PDFInfo
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Abstract
The invention discloses a bioelectric signal and spinal activity detection method, device and system, wherein the detection method comprises the following steps: collecting and processing bioelectric signal data of the back muscle group of the person to be tested; acquiring spinal motion state data of a person to be tested; and finally, based on the back muscle group bioelectric signal data and the spine movement state data of the tested person, resolving and analyzing the back muscle force and the spine movement degree of the tested person to obtain the spine movement degree data of the tested person, and simultaneously obtaining the back muscle force data of the tested person. The bioelectric signal and spine activity detection method can realize dynamic real-time monitoring of the back muscle force and spine state of a person to be detected, can be applied to detection and prevention and treatment of spine degeneration deformity state of the elderly, and can also be applied to sports science and rehabilitation treatment; the invention also discloses a device and a system adopting the method.
Description
Technical Field
The invention belongs to the field of human health detection, and particularly relates to a method, a device and a system for detecting bioelectricity signals and spinal activity.
Background
With the age, the spine of the old can be degenerated, the spine deformity can accelerate to progress due to the atrophy and the fat of the back muscle, the spine deformity can cause the activity change of the spine, the degeneration of the spine deformity of the old is evaluated in early stage, the degeneration deformity state of the old can be found as early as possible, the rehabilitation intervention can be carried out as early as possible, and the further progress of the deformity can be slowed down or even prevented.
However, the current evaluation of the degeneration and deformity state of the spine of the old is mainly finished by inquiring the illness state of a clinician, especially an orthopedics doctor, and the evaluation method is single, and the imaging technology including X-ray film, CT and nuclear magnetic resonance examination is adopted, so that the radiation or the high cost is detected, and the static detection methods can not reflect the dynamic change of the spine.
The accurate measurement of the strength and endurance of the trunk muscles is significant for the maintenance, prevention and treatment of the sagittal balance of the elderly patient; muscle strength and muscle endurance can be obtained by an electric signal feedback instrument, and a traditional electromyography acquisition method is to insert a needle electrode into muscle tissue for acquisition, and the method is traumatic and cannot exercise severely; in addition, the current instrument for collecting surface myoelectricity in China has the problems of inconvenience in carrying, influence on activities, easiness in line interference, incapability of dynamically monitoring data in real time, lack of a third party reminding and early warning function and the like.
Disclosure of Invention
In view of the above problems, the invention provides a device for detecting the health condition of the spine, which can dynamically detect the back muscle force and the activity of the spine of a person, thereby obtaining objective evaluation of the back muscle force and the health condition of the spine of the person to be detected.
The invention discloses a bioelectric signal and spinal activity detection method, which comprises the following steps:
collecting bioelectric signal data of the back muscle group of the person to be tested;
processing the collected bioelectric signal data;
acquiring spinal motion state data of a person to be tested;
and resolving and analyzing the back muscle strength and the spinal activity degree of the person to be tested based on the bioelectric signal data and the spinal motion state data of the back muscle group of the person to be tested.
The biological electric signal data of the back muscle group of the tested person is collected, and particularly the surface electric signal of the back muscle group of the tested person is collected.
The further improvement is that the process for processing the collected bioelectric signal data specifically comprises the following steps:
carrying out differential amplification on the collected surface electromyographic signals;
carrying out filtering treatment on power frequency interference components in the surface electromyographic signals after differential amplification;
baseline drift and jitter are eliminated;
eliminating high-frequency noise;
and performing automatic gain control processing on the surface electromyographic signals with different strengths at different positions.
The further improvement is that the spine movement state data comprise movement acceleration and movement angular velocity, and the obtaining the spine movement state data of the testee specifically comprises:
collecting movement acceleration and movement angular velocity data of a tested person in the spinal bending process;
calibrating the collected movement acceleration and movement angular velocity data;
and carrying out smooth filtering processing on the motion acceleration and the motion angular velocity data obtained after calibration.
A further improvement is that the specific process of obtaining the back muscle strength and the spinal activity degree of the tested person through the solution comprises the following steps:
according to the acquired back muscle group bioelectric signal data and spine movement state data of the person to be tested, a human spine musculoskeletal biomechanical model of the person to be tested is established;
analyzing and resolving the back muscle strength of the person to be tested, and analyzing and resolving the motion amplitude, the motion speed and the motion intensity of the person to be tested in the spinal bending process.
The invention also provides a bioelectric signal and spinal activity detection device, comprising:
the bioelectric signal acquisition module is used for acquiring bioelectric signal data of the back muscle group of the to-be-detected person and transmitting the bioelectric signal data to the bioelectric signal processing module;
the bioelectric signal processing module is used for receiving and processing the bioelectric signal data and transmitting the processed bioelectric signal data to the communication module;
the gesture sensing module is used for acquiring spinal motion state data of the person to be tested and transmitting the spinal motion state data to the communication module;
the communication module is used for transmitting the received spinal motion state data and bioelectric signal data to the resolving module;
the resolving module is used for receiving the spine movement state data and the processed bioelectric signals, and resolving and analyzing the back muscle strength and the spine movement degree of the person to be tested;
the bioelectric signal acquisition module is in communication connection with the bioelectric signal processing module, and the bioelectric signal processing module and the gesture sensing module are in communication connection with the communication module; the communication module is in communication connection with the resolving module.
The further improvement is that: the bioelectric signal acquisition module adopts a silver chloride surface electrode, and the acquired bioelectric signal is a surface electromyographic signal of the back muscle group of the person to be detected.
A further improvement is that the bioelectric signal processing module comprises:
the variable voltage gain differential amplifier is used for carrying out differential amplification on the collected surface electromyographic signals;
the power frequency trap is used for filtering power frequency interference components in the surface electromyographic signals after differential amplification;
the constant drift filter is used for eliminating baseline drift and jitter;
a high frequency noise filter for eliminating high frequency noise;
and the fine automatic gain controller is used for processing the surface electromyographic signals of different positions and different intensity of the back muscle groups of the tested person.
The further improvement is that: the spine movement state data specifically comprise movement acceleration data and movement angular velocity data of the spine of the tested person.
The invention also provides a bioelectric signal and spinal activity detection system, which comprises the bioelectric signal and spinal activity detection device.
The invention relates to a bioelectric signal and spine activity detection method, which is used for collecting and processing bioelectric signal data of back muscle groups of a to-be-detected person; acquiring spinal motion state data of a person to be tested; finally, based on the back muscle group bioelectric signal data and the spine movement state data of the tested person, resolving and analyzing the back muscle force and the spine movement degree of the tested person to obtain the spine movement degree data of the tested person, and simultaneously obtaining the back muscle force data of the tested person; compared with the existing back muscle strength detection method and spine health condition detection method, the biological electric signal and spine activity detection method of the invention is not dependent on doctors or the existing medical auxiliary detection, can realize the dynamic detection of the back muscle strength and spine state of a person to be detected directly, obtains objective detection results, greatly improves the convenience degree of spine activity detection, can be applied to detection and prevention treatment of the spine degeneration malformation state of the elderly, and can also be applied to sports science and rehabilitation treatment. The invention also discloses a device and a system adopting the method, and the device and the system have all the beneficial effects of the method.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 illustrates a system block diagram of a bioelectric signal and spinal activity detection device according to an embodiment of the invention;
fig. 2 shows a block diagram of a bioelectric signal acquisition module and a bioelectric signal processing module according to an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention discloses a bioelectric signal and spinal activity detection method, which comprises the following steps:
collecting bioelectric signal data of the back muscle group of the person to be tested;
processing the collected bioelectric signal data;
acquiring spinal motion state data of a person to be tested;
and resolving and analyzing the back muscle force and the spinal activity degree of the person to be tested based on the back muscle group bioelectric signal data and the spinal motion state data of the person to be tested.
The back muscle strength data and the spine activity data of the tested person can be obtained simultaneously by the method; compared with the existing back muscle strength detection method and spine health condition detection method, the bioelectric signal and spine activity detection method can be used for directly detecting the back muscle strength and spine state of a person to be detected without depending on doctors or the existing medical auxiliary detection, further objective evaluation can be carried out on the spine state and back muscle strength state of the person to be detected, the convenience degree of spine activity detection is greatly improved, the method can be applied to detection and prevention and treatment of spine degeneration malformation states of old people, the back muscle strength detection can be used for judging the rehabilitation degree of a patient by comparing the muscle strength before and after operation, and the method can be used for sports science and rehabilitation treatment.
The further improvement is that the bioelectric signal data of the back muscle group of the person to be detected is collected, in particular to the surface myoelectric signal of the back muscle group of the person to be detected.
A further improvement is that the process of processing the collected bioelectric signal data specifically comprises:
carrying out differential amplification on the collected surface electromyographic signals;
carrying out filtering treatment on power frequency interference components in the surface electromyographic signals after differential amplification;
baseline drift and jitter are eliminated;
eliminating high-frequency noise;
and performing automatic gain control processing on the surface electromyographic signals with different strengths at different positions.
The processing process can make the collected surface electromyographic signals of different parts of the back of the to-be-detected person balanced in strength comparison, and can filter invalid data, so that the accuracy of the collected surface electromyographic signal data is ensured, and the reliability is improved.
The further improvement is that the spine movement state data comprise movement acceleration and movement angular velocity, and the obtaining of the spine movement state data of the person to be tested specifically comprises the following steps:
collecting movement acceleration and movement angular velocity data of a tested person in the spinal bending process;
calibrating the collected movement acceleration and movement angular velocity data;
and carrying out smooth filtering processing on the motion acceleration and the motion angular velocity data obtained after calibration. By collecting the movement state data of the spine, the problems that the detection methods in the prior art are all static detection and cannot reflect the dynamic change of the spine are solved.
A further improvement is that the specific process of calculating the back muscle strength and the spinal activity of the tested person comprises the following steps:
according to the acquired back muscle group bioelectric signal data and spine movement state data of the person to be tested, a human spine musculoskeletal biomechanical model of the person to be tested is established;
analyzing and resolving the back muscle strength of the person to be tested, and analyzing and resolving the motion amplitude, the motion speed and the motion intensity of the person to be tested in the spinal bending process.
And the biomechanical model of the person to be detected is combined to carry out calculation, so that the reliability of the detection result is further improved.
As shown in FIG. 1, the invention also provides a bioelectric signal and spinal activity detection device, which comprises a bioelectric signal acquisition module, a bioelectric signal processing module, a posture sensing module, a communication module and a resolution module. The bioelectric signal acquisition module is in communication connection with the bioelectric signal processing module, the bioelectric signal processing module and the gesture sensing module are both in communication connection with the communication module, and the communication module is in communication connection with the resolving module.
Wherein: referring to fig. 2, the bioelectric signal acquisition module is configured to acquire bioelectric signal data of a back muscle group of a person to be tested and transmit the bioelectric signal data to the bioelectric signal processing module; in a preferred embodiment of the invention, the bioelectric signal acquisition module adopts a silver chloride (AgCl) surface electrode, the acquired bioelectric signal is a surface myoelectric signal of a back muscle group of a person to be detected, and the AgCl surface electrode has biocompatibility, is safe and noninvasive, is simple to use, and is suitable for long-time omnibearing detection, in particular myoelectric measurement during exercise.
The bioelectric signal processing module is used for receiving and processing bioelectric signal data and transmitting the processed bioelectric signal data to the communication module;
as shown in fig. 2, the bioelectric signal processing module of the present invention includes, in communication connection:
the variable voltage gain differential amplifier is used for carrying out differential amplification on the collected surface electromyographic signals, the common mode rejection ratio is more than 140dB, the offset voltage is less than 50uV, and the input has ESD protection, so that common mode interference can be effectively inhibited;
the power frequency trap is used for filtering power frequency interference components in the surface electromyographic signals after differential amplification; specifically, in one embodiment of the invention, a double T trap is used to effectively suppress 50Hz power frequency interference in a signal.
A constant drift filter for eliminating baseline drift and jitter that may occur;
a high frequency noise filter for eliminating high frequency noise; specifically, the high-frequency filter adopts a Sallen-Key structure, so that steeper transition zone change and stable signal are ensured.
And the fine automatic gain controller is used for processing the surface electromyographic signals of different positions and different intensity of the back muscle groups of the tested person. The fine automatic gain controller has the characteristic of programmable gain, and ensures that the device realizes the acquisition and processing of the surface electromyographic signals with different strengths at different parts.
The bioelectric signal processing module simultaneously adopts a variable voltage gain differential amplifier with high common mode rejection ratio, a power frequency trap, a high-frequency noise filter and a constant drift filter, so that noise is effectively reduced, and common mode rejection capability is improved; the fine automatic gain controller ensures that the device realizes the collection and the processing of myoelectric signals with different intensity at different positions.
The gesture sensing module is used for acquiring spinal motion state data of the person to be tested and transmitting the spinal motion state data to the communication module; specifically, the spinal motion state data specifically includes a motion acceleration and a motion angular velocity of the spinal column of the subject. In the specific embodiment of the invention, the gesture sensing module consists of a mes inertial chip and an acquisition and communication circuit thereof. The device mainly realizes the collection, calibration, filtering and transmission of the motion acceleration and the motion angular velocity; the preliminarily acquired spinal motion acceleration and motion angular velocity values may have noise, and the accuracy of the obtained spinal motion acceleration and motion angular velocity after calibration and filtering treatment is higher, so that the reliability of the detection result of the device is higher.
The communication module is used for transmitting the received spinal motion state data and bioelectric signal data to the resolving module; the communication module is a wireless communication module; according to a specific embodiment of the invention, the communication module is realized by a wireless low-power-consumption data transmission device, the wireless low-power-consumption data transmission device consists of a low-power-consumption Bluetooth chip and a peripheral circuit thereof, and a communication protocol sent by the communication module is a low-power-consumption Bluetooth 5.0 protocol; the wireless low-power consumption Bluetooth communication module in the embodiment has the advantages of convenience and low power consumption, the latest version of Bluetooth 5.0 transmission distance can reach 150 meters, bluetooth communication is mainly used for connecting some external electronic equipment or short-distance data transmission, the limitation of connecting various digital equipment by using a cable is broken, and the device can realize the wearable effect more conveniently than the wired transmission mode when being applied to the detection device.
And the resolving module is used for receiving the spinal motion state data and the processed bioelectric signals, and resolving and analyzing the back muscle strength and the spinal activity of the person to be tested.
As shown in fig. 1, according to a preferred embodiment of the present invention, the bioelectric signal and spinal activity detection device further includes a display module, where the display module is communicatively connected to the calculation module and the communication module, and the spinal motion state data and the surface electromyographic signal data are transmitted to the display module for real-time display through the wireless low-power-consumption data transmission device; the back muscle strength and the spinal activity data of the tested person obtained by the calculation of the calculation module can be displayed.
According to a preferred embodiment of the present invention, referring to fig. 1, the detection apparatus of the present invention further comprises a power module for supplying power to the bioelectric signal and the spinal activity detection apparatus, the power module including a lithium battery and a low power consumption power management unit.
The lithium battery adopts a polymer lithium battery with small volume and light weight, and can be repeatedly charged.
The low-power consumption power management unit consists of a power chip and peripheral circuits thereof. The power supply chip adopts a chip with low quiescent current and low working current, and simultaneously selects a proper low-power consumption analog operational amplifier, and the power consumption of the system is effectively reduced by selecting a system architecture with higher power consumption utilization rate.
The invention also provides a bioelectric signal and spinal activity detection system, which comprises the bioelectric signal and spinal activity detection device.
The invention can be widely applied to communities, monitors the spine state of the old, evaluates the spine degeneration degree of the old, not only can prevent and delay the disease development in early stage and realize the forward movement of diagnosis and treatment gateways, but also can provide key quantitative measurement index support for the surgical treatment of patients with serious distortion.
In sports science and rehabilitation therapy, exercise muscle fatigue analysis is a popular topic of great concern in the related fields of sports, medicine, rehabilitation and the like, and a plurality of institutions aim at finding out a method for evaluating the muscle fatigue degree, so that a perfect training plan or rehabilitation course is formulated.
In addition, the method for acquiring the combined gesture sensing information by adopting the surface myoelectricity can actually monitor the activity states of multiple local muscles of the human body simultaneously, is not limited to the muscle groups of the back, is applied to physical exercise and rehabilitation training of patients, and can obtain the coordinated action mechanisms and exertion degrees of different muscles in the movement state, thereby correcting the false actions and avoiding the conditions of excessive training and the like.
Although the 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. A method for detecting bioelectrical signals and spinal activity, comprising the steps of:
the bioelectric signal data of the muscle group of the back of the person to be detected is collected through the silver chloride surface electrode, and the bioelectric signal data specifically comprises: collecting surface electromyographic signals of back muscle groups of a person to be tested;
processing the collected bioelectric signal data specifically comprises the following steps: carrying out differential amplification on the collected surface electromyographic signals; carrying out filtering treatment on power frequency interference components in the surface electromyographic signals after differential amplification; baseline drift and jitter are eliminated; a Sallen-Key structure high-frequency noise filter is adopted to eliminate high-frequency noise; carrying out automatic gain control processing on the surface electromyographic signals with different strengths at different positions;
the method comprises the steps of obtaining spinal motion state data of a person to be tested, wherein the spinal motion state data comprise motion acceleration and motion angular velocity, and the step of obtaining the spinal motion state data of the person to be tested comprises the following specific steps: collecting movement acceleration and movement angular velocity data of a tested person in the spinal bending process; calibrating the collected movement acceleration and movement angular velocity data; carrying out smooth filtering treatment on the motion acceleration and the motion angular velocity data obtained after calibration;
based on the bioelectric signal data and the spine movement state data of the back muscle group of the person to be tested, resolving and analyzing the back muscle force and the spine movement degree of the person to be tested, wherein the specific process of resolving to obtain the back muscle force and the spine movement degree of the person to be tested comprises the following steps: according to the acquired back muscle group bioelectric signal data and spine movement state data of the person to be tested, a human spine musculoskeletal biomechanical model of the person to be tested is established; analyzing and resolving the back muscle strength of the person to be tested, and analyzing and resolving the motion amplitude, the motion speed and the motion intensity of the person to be tested in the spinal bending process.
2. A bioelectric signal and spinal activity detection device, comprising:
the bioelectric signal acquisition module is used for acquiring bioelectric signal data of the back muscle group of the to-be-detected person and transmitting the bioelectric signal data to the bioelectric signal processing module, and the acquired bioelectric signal is a surface myoelectric signal of the back muscle group of the to-be-detected person; the bioelectric signal acquisition module adopts a silver chloride surface electrode;
the bioelectric signal processing module is used for receiving and processing the bioelectric signal data and transmitting the processed bioelectric signal data to the communication module; the bioelectric signal processing module comprises the following components which are connected in sequence in a communication mode: the variable voltage gain differential amplifier is used for carrying out differential amplification on the collected surface electromyographic signals; the power frequency trap is used for filtering power frequency interference components in the surface electromyographic signals after differential amplification; the constant drift filter is used for eliminating baseline drift and jitter; a high frequency noise filter for eliminating high frequency noise; the fine automatic gain controller is used for processing surface electromyographic signals of different positions and different intensity of back muscle groups of the person to be tested; wherein, the high-frequency noise filter adopts a Sallen-Key structure;
the gesture sensing module is used for acquiring spinal motion state data of the person to be tested and transmitting the spinal motion state data to the communication module; the spine movement state data comprise movement acceleration and movement angular velocity, and the step of obtaining the spine movement state data of the tested person specifically comprises the following steps: collecting movement acceleration and movement angular velocity data of a tested person in the spinal bending process; calibrating the collected movement acceleration and movement angular velocity data; carrying out smooth filtering treatment on the motion acceleration and the motion angular velocity data obtained after calibration;
the communication module is used for transmitting the received spinal motion state data and bioelectric signal data to the resolving module;
the resolving module is used for receiving the spine movement state data and the processed bioelectric signals, and resolving and analyzing the back muscle strength and the spine movement degree of the person to be tested; the specific process for obtaining the back muscle strength and the spinal activity degree of the tested person through the solution comprises the following steps: according to the acquired back muscle group bioelectric signal data and spine movement state data of the person to be tested, a human spine musculoskeletal biomechanical model of the person to be tested is established; analyzing and resolving the back muscle strength of the person to be tested, and analyzing and resolving the motion amplitude, the motion speed and the motion strength of the person to be tested in the spinal bending process;
the bioelectric signal acquisition module is in communication connection with the bioelectric signal processing module, and the bioelectric signal processing module and the gesture sensing module are in communication connection with the communication module; the communication module is in communication connection with the resolving module.
3. A bioelectrical signal and spinal activity detection system comprising the bioelectrical signal and spinal activity detection apparatus of claim 2.
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| CN107137080A (en) * | 2017-05-25 | 2017-09-08 | 中国科学院深圳先进技术研究院 | Chronic back pain patient muscle's active state determination methods and system |
| CN109804331A (en) * | 2016-12-02 | 2019-05-24 | 皮松科技股份有限公司 | Bodily tissue electric signal is detected and used |
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| CN1883387A (en) * | 2006-06-30 | 2006-12-27 | 中国科学院合肥物质科学研究院 | Distributed human motion link acceleration testing device |
| WO2013177592A2 (en) * | 2012-05-25 | 2013-11-28 | Emotiv Lifesciences, Inc. | System and method for providing and aggregating biosignals and action data |
| CN103054585A (en) * | 2013-01-21 | 2013-04-24 | 杭州电子科技大学 | Biological motion information based upper limb shoulder elbow wrist joint motion function evaluation method |
| CN109804331A (en) * | 2016-12-02 | 2019-05-24 | 皮松科技股份有限公司 | Bodily tissue electric signal is detected and used |
| CN107137080A (en) * | 2017-05-25 | 2017-09-08 | 中国科学院深圳先进技术研究院 | Chronic back pain patient muscle's active state determination methods and system |
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