CN113576467A - Wearable real-time gait detection system integrating plantar pressure sensor and IMU - Google Patents
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Abstract
The invention discloses a wearable real-time gait detection system integrating a plantar pressure sensor and an IMU (inertial measurement Unit), which comprises: one end of the plantar pressure sensor is connected with the control module, an analog signal is converted into a digital signal through a conversion circuit carried by the plantar pressure sensor and transmitted to the control module, and the control module is simultaneously connected with the IMU, is installed on the fixing device together and is placed at the position where the shank is stable; the control module uses a self-grinding gait phase detection algorithm and is used for calculating a gait phase analysis result in real time and transmitting the phase detection result, the underfoot pressure change information, the limb kinematics information and the posture direction information data to the upper computer. The gait analysis system is used for assisting professional doctors, guardians and patients to detect and analyze the gait condition of the wearer in real time, and increasing the data dimension of the wearer on the premise of not influencing daily activities, thereby being beneficial to deep analysis.
Description
Technical Field
The invention relates to the field of lower limb gait detection and control, in particular to a wearable real-time gait detection system integrating a plantar pressure sensor and an IMU (Inertial Measurement Unit).
Background
Gait refers to the movement and posture of a person when walking, and is closely related to the health conditions of the bone, muscle and nervous system of the person. Neurological diseases such as stroke and parkinson often cause lower limb gait disorder, and seriously affect the daily life of patients. Clinicians adopt a gait assessment method to evaluate the disease progress, falling risk and functional rehabilitation of patients, so as to formulate a more detailed and personalized rehabilitation method and promote the rehabilitation of patients.
Traditional gait detection methods, such as a step-top gait analyzer, are expensive and subject to great limitations by the experimental environment.
Disclosure of Invention
The invention provides a wearable real-time gait detection system integrating plantar pressure sensors and an IMU (inertial measurement Unit), which is used for assisting professional doctors, guardians and patients to carry out real-time detection and analyzing the gait condition of a wearer, increasing the data dimension of the system on the premise of not influencing daily activities, and facilitating deep analysis, and is described in detail as follows:
a wearable real-time gait detection system fusing plantar pressure sensors and an IMU, the system comprising: the device comprises a plantar pressure sensor, an IMU, a control module and a fixing device.
One end of the plantar pressure sensor is connected with the control module, an analog signal is converted into a digital signal through a conversion circuit carried by the plantar pressure sensor and transmitted to the control module, and the control module is simultaneously connected with the IMU, is installed on the fixing device together and is placed at the position where the shank is stable;
the control module uses a self-grinding gait phase detection algorithm and is used for calculating a gait phase analysis result in real time and transmitting the phase detection result, the underfoot pressure change information, the limb kinematics information and the posture direction information data to the upper computer.
Wherein, the control module detects gait events according to the change information of the underfoot pressure: the heel touches the ground, the full foot touches the ground, the heel leaves the ground and the toes leave the ground;
the IMU continuously collects the shank kinematics information and judges the middle period of the swing phase according to the angular velocity during the swing phase.
Further, the IMU includes: a three-axis accelerometer, a three-axis angular accelerometer, and a three-axis magnetometer.
Wherein, 8 force-sensitive sensors are distributed on the plantar pressure sensor, 3 sensors at the heel are a group of sensor arrays, and 5 sensors at the arch and the front sole are a group; the sensors within a group are connected using an or gate;
when the state parameter of the sensor array at the heel is 1 and the state parameter of the front foot group is 0, detecting that the gait event is heel landing;
when the state of the heel group is 1 and the state of the forefoot group is 1, detecting that the gait event is full-foot landing; when the state of the heel group is 0 and the state of the forefoot group is 1, detecting that the gait event is heel off; when the state of the heel group is 0 and the state of the forefoot group is 0, the gait event is detected to be toe-off, and the gait enters the swing phase.
Further, the self-research gait phase detection algorithm is as follows:
using an IMU (inertial measurement Unit), extracting calf angular velocity change information in real time, establishing a sliding window, detecting a peak point, establishing a judgment window, wherein the judgment window comprises a current angular velocity value acquired in real time and angular velocity values at the previous three moments, and the angular velocity values are t1, t2, t3 and t4 in time sequence, wherein t4 is the current moment point, the angular velocities are respectively omega (i-3), omega (i-2), omega (i-1) and omega (i), and meanwhile, the default parameter detection frequency is 100 Hz;
firstly, entering a peak detection protection program, judging the time from the last peak point, if the time is shorter than 0.3s, namely index is less than 0, not carrying out peak detection, waiting for the completion of the protection program, and starting the protection program when the peak is detected each time;
when the program passes through the protection time, calculating the difference value of the angular speed between the time point t2 and the time point t 1:
w1＝ω(i-2)-ω(i-3)；
calculating the difference value between the time point t3 and the time point t 2: w2 ═ ω (i-1) - ω (i-2);
calculating the difference w3 between the time point t4 and the time point t2 as ω i- ω (i-2);
when w1 is less than 0, w2 is more than or equal to 0, w3 is less than 0, and the angular velocity value at the time point t2 is greater than the self-set threshold, the time point t2 is the target peak point, and the protection program starts again to set index to be 30;
when gait is analyzed in real time, the calculation of the gait phase is completed through the control module, and gait phase detection results, kinematic parameters and posture direction information are sent to the upper computer through the carried Bluetooth at 100 Hz.
Further, the control module includes: nRF52832 chip, conversion circuitry, bluetooth,
the nRF52832 chip is used for calculating a gait phase analysis result in real time; the conversion circuit is used for converting the acquired analog signals into digital signals; the Bluetooth is used for transmitting gait phase detection results, underfoot pressure change information, limb kinematics information and posture direction information data to the upper computer.
The technical scheme provided by the invention has the beneficial effects that:
1. according to the gait phase judging method, the fusion signal of the plantar pressure sensor and the single IMU is used as the judging basis of the gait phase, so that the practicability of the algorithm is improved, the movement information dimensionality is increased, and a basis can be provided for the deep analysis of subsequent gaits;
2. the invention can complete real-time detection through the insole pressure sensor in the standing phase and complete detection on the middle phase of the swing phase through a sliding window algorithm in the swing phase by establishing gait phase detection, wherein the detection rate of the gait phase and the accuracy of peak detection are both 100%, and delay can be reduced by increasing data updating frequency; the algorithm threshold can be adjusted externally according to the weight of the wearer and the personal exercise habits, and the applicability of the algorithm is improved.
Drawings
Fig. 1 is a schematic structural diagram of a wearable real-time gait detection system incorporating plantar pressure sensors and IMUs;
fig. 2 is a wearing schematic diagram of a wearable real-time gait detection system incorporating plantar pressure sensors and IMUs;
FIG. 3 is a schematic diagram of the self-grinding gait phase detection algorithm of the whole system;
fig. 4 is a schematic diagram of a sliding window algorithm.
In the drawings, the components represented by the respective reference numerals are listed below:
1: a plantar pressure sensor; 2: an IMU;
3: a control module; 4: and (4) a fixing device.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
With the rapid development of sensing and electronic manufacturing technology, the portability and light weight of the gait detection system are both satisfied. Common sensors for gait detection systems include two types: plantar pressure sensors and IMUs. The plantar pressure sensor can measure the plantar pressure change of a wearer in the walking process; the IMU can measure the kinematics information and the posture direction information such as limb acceleration, angular velocity and the like in the walking process of a wearer.
The sole pressure sensor has the advantages of visual data and simple algorithm, can be directly integrated into the insole or between the insole and the sole, has attractive design and is often used as the gold standard of a gait detection system. However, the sole pressure sensor provides a single datum, and during the swing phase, it cannot provide effective information because of the absence of ground reaction. The IMU can provide motion information with more dimensions, make up for the loss of swing phase input signals, and increase the data depth of standing phase signals, thereby facilitating depth analysis. Therefore, the embodiment of the invention provides a wearable real-time gait detection system fusing a plantar pressure sensor and an IMU.
Example 1
The embodiment of the invention provides a wearable real-time gait detection system integrating a plantar pressure sensor and a single IMU, which comprises: plantar pressure sensor 1, IMU2, control module 3, and fixture 4. The system uses a self-research gait phase detection algorithm for realizing real-time detection and analysis of gait phase and kinematic information, and can be transmitted to an upper computer through Bluetooth to be used as a gait input and feedback part of other systems, for example: functional Electrical Stimulation (FES) systems, lower extremity exoskeleton systems, or other systems that require the use of gait phase information and motion information.
Wherein, 8 force-sensitive sensors are distributed on the sole pressure sensor 1, and the sole pressure sensor 1 is designed according to the size of the national standard insole, can be placed in shoes with the same model and is positioned between the insole and the sole.
Wherein, IMU2 includes: a three-axis accelerometer, a three-axis angular accelerometer, and a three-axis magnetometer.
The control module 3 is provided with a self-designed high integrated circuit which contains a conversion circuit and a Bluetooth chip and is used for synchronizing and controlling other modules (the plantar pressure sensor 1 and the IMU2), calculating a gait phase analysis result in real time and transmitting the phase detection result, underfoot pressure change information, limb kinematics information and posture direction information data to an upper computer.
One end of the plantar pressure sensor 1 is connected with the control module 3, an analog signal is converted into a digital signal through a conversion circuit carried by the plantar pressure sensor and transmitted to the control module 3 (for example, the model of a single chip microcomputer is nRf52832), and the control module 3 is simultaneously connected with the IMU2, is installed on the fixing device 4 and is placed at the stable part of the crus.
The working principle of the embodiment of the invention is as follows: the gait detection system of the wearable real-time gait detection system designed for wearing on both legs of a patient transmits pressure change information to the control module 3 by the plantar pressure sensor 1 when walking, and the control module 3 can detect gait events according to the pressure information: the heel touches the ground, the full foot touches the ground, the heel leaves the ground, and the toes leave the ground. Meanwhile, the IMU2 continuously collects the calf kinematics information and judges the swing phase middle period from the angular velocity during the swing phase.
Example 2
The solution of example 1 is further described below with reference to fig. 1 and 2, and is described in detail below:
the sole pressure sensor 1 is distributed with 8 force-sensitive sensors for measuring the sole pressure change when the wearer walks, and the interference to the wearer can not be generated. Further, in the embodiment of the invention, 8 force-sensitive sensors are divided into two groups, 3 sensors at the heel are a group of sensor arrays, 5 sensors at the arch and the forefoot are a group, and the gait state is judged by using a threshold algorithm. The sensors in the group are connected using an or gate, taking the heel group as an example: when the parameter of any one force-sensitive sensor in the 3 force-sensitive sensors reaches the threshold value, the output of the heel group is changed from 0 to 1, and in specific application, the threshold value is set according to the position of the sensor, and online upgrade can be realized.
When a wearer walks, when the state parameter of the plantar pressure sensor array of the heel group is 1 and the state parameter of the forefoot group is 0, the detected gait event is heel landing.
Similarly, when the heel group is in the state of 1 and the forefoot group is in the state of 1, the gait event is detected to be full-foot landing. When the state of the heel group is 0 and the state of the forefoot group is 1, the gait event is detected to be heel off. When the state of the heel group is 0 and the state of the forefoot group is 0, the gait event is detected as toe-off.
After toe-off, gait enters the swing phase, at which point there is no ground reaction. The embodiment of the invention develops and designs a sliding window gait detection algorithm suitable for a swing phase: and (3) using the IMU to extract the angular velocity change information of the crus in real time, establishing a 40ms sliding window and detecting a peak point. The self-research algorithm has reached 100% detection rate and 100% peak detection accuracy for the middle phase of the wobble phase within 20ms delay, and includes a detection protection procedure.
Referring to fig. 4, the self-grinding sliding window algorithm is:
and establishing a judgment window which comprises the current angular velocity value acquired in real time and the angular velocity values at the first three moments. The time sequence of the parameter detection is t1, t2, t3 and t4, wherein t4 is the current time point, the angular speeds of the current time point are respectively omega (i-3), omega (i-2), omega (i-1) and omega (i), and the default parameter detection frequency is 100 Hz.
The method comprises the steps of firstly entering a peak detection protection program, judging the time from the last peak point, if the time is shorter than 0.3s, namely index is less than 0, not carrying out peak detection, waiting for the completion of the protection program, and starting the protection program when the peak value is detected each time.
When the program passes through the protection time, calculating the difference value of the angular speed between the time point t2 and the time point t 1:
w1＝ω(i-2)-ω(i-3)；
calculating the difference value between the time point t3 and the time point t 2: w2 ═ ω (i-1) - ω (i-2);
calculating the difference value between the time point t4 and the time point t 2: w3 ═ ω i- ω (i-2).
When w1 is less than 0, w2 is greater than or equal to 0, w3 is less than 0, and the angular velocity value at the time point t2 is greater than the self-set threshold, the time point t2 is the target peak point, and the protection program starts the setting index again to be 30.
When gait is analyzed in real time, the calculation of the gait phase is completed through the control module 3, and gait phase detection results, kinematic parameters and posture direction information are sent to an upper computer at 100Hz through the carried Bluetooth.
The control module is provided with an nRF52832 chip, a conversion circuit and Bluetooth. The nRF52832 chip is used for synchronizing and controlling other modules and calculating a gait phase analysis result in real time; the conversion circuit is used for converting the acquired analog signals into digital signals; the Bluetooth is used for transmitting gait phase detection results, underfoot pressure change information, limb kinematics information and posture direction information data to the upper computer. The control module has the advantages of small volume and high integration.
Meanwhile, the wearable real-time gait detection system designed by the embodiment of the invention can externally adjust the algorithm threshold according to the weight and the personal motion habit of a wearer, and can improve the algorithm applicability.
In the embodiment of the present invention, except for the specific description of the model of each device, the model of other devices is not limited, as long as the device can perform the above functions.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (6)
1. A wearable real-time gait detection system fusing plantar pressure sensors and IMU, the system comprising: a sole pressure sensor is arranged on the sole of the foot,
one end of the plantar pressure sensor is connected with the control module, an analog signal is converted into a digital signal through a conversion circuit carried by the plantar pressure sensor and transmitted to the control module, and the control module is simultaneously connected with the IMU, is installed on the fixing device together and is placed at the position where the shank is stable;
the control module uses a self-grinding gait phase detection algorithm and is used for calculating a gait phase analysis result in real time and transmitting the phase detection result, the underfoot pressure change information, the limb kinematics information and the posture direction information data to the upper computer.
2. The wearable real-time gait detection system with the plantar pressure sensor and the IMU fused according to claim 1, wherein the control module detects gait events according to the foot pressure change information: the heel touches the ground, the full foot touches the ground, the heel leaves the ground and the toes leave the ground;
the IMU continuously collects the shank kinematics information and judges the middle period of the swing phase according to the angular velocity during the swing phase.
3. The system of claim 1, wherein the IMU comprises: a three-axis accelerometer, a three-axis angular accelerometer, and a three-axis magnetometer.
4. The wearable real-time gait detection system with the combination of plantar pressure sensors and IMU according to claim 1, characterized in that 8 force-sensitive sensors are distributed on the plantar pressure sensors, 3 sensors at the heel are a group of sensor arrays, and 5 sensors of the arch and forefoot are a group; the sensors within a group are connected using an or gate;
when the state parameter of the sensor array at the heel is 1 and the state parameter of the front foot group is 0, detecting that the gait event is heel landing;
when the state of the heel group is 1 and the state of the forefoot group is 1, detecting that the gait event is full-foot landing; when the state of the heel group is 0 and the state of the forefoot group is 1, detecting that the gait event is heel off; when the state of the heel group is 0 and the state of the forefoot group is 0, the gait event is detected to be toe-off, and the gait enters the swing phase.
5. The system of claim 1, wherein the self-developed gait phase detection algorithm is:
using an IMU (inertial measurement Unit), extracting calf angular velocity change information in real time, establishing a sliding window, detecting a peak point, establishing a judgment window, wherein the judgment window comprises a current angular velocity value acquired in real time and angular velocity values at the previous three moments, the angular velocity values are t1, t2, t3 and t4 in time sequence, t4 is the current moment point, the angular velocities are respectively omega (i-3), omega (i-2), omega (i-1) and omega (i), and meanwhile, the default parameter detection frequency is 100 Hz;
firstly, entering a peak detection protection program, judging the time from the last peak point, if the time is shorter than 0.3s, namely index is less than 0, not carrying out peak detection, waiting for the completion of the protection program, and starting the protection program when the peak is detected each time;
when the program passes through the protection time, calculating the difference w1 between the angular speed at the time point t2 and the angular speed at the time point t1 as omega (i-2) -omega (i-3); calculating the difference w2 between the time point t3 and the time point t2 as ω (i-1) - ω (i-2); calculating the difference w3 between the time point t4 and the time point t2 as ω i- ω (i-2);
when w1 is less than 0, w2 is more than or equal to 0, w3 is less than 0, and the angular velocity value at the time point of t2 is greater than the self-set threshold, the time point of t2 is the target peak point, and the protection program starts again to set index to be 30;
when gait is analyzed in real time, the calculation of the gait phase is completed through the control module, and gait phase detection results, kinematic parameters and posture direction information are sent to the upper computer through the carried Bluetooth at 100 Hz.
6. The system of claim 5, wherein the control module comprises: nRF52832 chip, conversion circuitry, bluetooth,
the nRF52832 chip is used for calculating a gait phase analysis result in real time; the conversion circuit is used for converting the acquired analog signals into digital signals; the Bluetooth is used for transmitting gait phase detection results, underfoot pressure change information, limb kinematics information and posture direction information data to the upper computer.
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