Portable gait analysis system based on inertial sensor

Abstract

The invention discloses a portable gait analysis system based on an inertial sensor. The portable gait analysis system comprises an IMU sensor array and a distributed data acquisition module, wherein the IMU sensor array is composed of nine inertial measurement units; the distributed data acquisition module comprises three independent acquisition units which are respectively connected with the inertial measurement units of the upper trunk, the left lower limb and the right lower limb and are used for acquiring corresponding data so as to realize partitioned data acquisition and storage; the inertial measurement units and the independent acquisition units are fixed on the body of a user through an integrated wearable structure. The scheme is based on the human body biomechanics principle, sensors are arranged at key nodes of human body motion, and the distribution scheme can comprehensively capture human body motion characteristics.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and particularly to a portable gait analysis system based on inertial sensors. Background Art

[0002] Foot and spinal diseases, as a common type of locomotor system diseases, mainly include idiopathic scoliosis, leg length discrepancy, and flat feet. These diseases not only affect the body structure of patients, but also have a significant impact on their motor function and quality of life. Although the causes and clinical manifestations are different, these diseases will cause changes in human gait. During normal walking, the human body maintains balance and efficiency by coordinating the movements of the trunk, hip, knee, and ankle joints. Any structural abnormality will lead to compensatory changes in the movement chain, and then form characteristic gait patterns. The kinematic analysis technology based on inertial measurement units (IMUs) provides a new technical path for the early screening of such diseases.

[0003] Idiopathic scoliosis is a complex three-dimensional spinal deformity, with an incidence rate of 1.5%-3% among adolescents aged 10-18 years, and the proportion of female patients is significantly higher than that of male patients. This disease shows unique kinematic characteristics during the gait cycle: due to the compensatory movement of the trunk caused by scoliosis, patients will show left-right asymmetry in the amplitude of trunk swing and abnormal relative movement of the scapula and pelvis during walking. Research has confirmed that by arranging IMU sensors at the scapula and sacrum, key motion parameters such as trunk offset, rotation, and roll angle of patients can be effectively captured, and these parameters can be quantitatively evaluated through the triaxial acceleration and angular velocity data collected by the IMU sensors.

[0004] Leg length discrepancy is mainly manifested as the asymmetry of the lower limb structure. Research shows that 90% of the population has different degrees of leg length differences. When the difference exceeds the clinical threshold (usually 0.5-2 cm), the gait of patients will show obvious abnormalities, specifically manifested as asymmetry in the time of the stance phase and swing phase, and compensatory movements of the hip and knee joints. By arranging IMU sensors on the thigh and calf, the changes in these spatio-temporal parameters and kinematic characteristics can be accurately recorded, thus providing an objective basis for the early screening of leg length discrepancy.

[0005] The main feature of flat feet is the reduction or disappearance of the longitudinal arch of the foot, with a relatively high incidence rate in children and adolescents. The gait abnormalities caused by this disease are mainly manifested in the change of the foot movement pattern: excessive varus occurs in the stance phase, and the power transmission efficiency in the propulsion phase is reduced. These changes will gradually affect the movement of the proximal joints, and ultimately lead to abnormal overall gait patterns. Arranging IMU sensors on the foot can effectively capture the foot movement acceleration spectrum and angular velocity characteristics of patients during walking, providing quantitative indicators for the screening of flat feet.

[0006] The above three foot and spine diseases have close pathological associations: flat feet can change the biomechanical pattern of the lower limbs and may lead to functional leg length inequality in some cases; significant leg length differences may cause pelvic tilt, which may in turn prompt the spine to make compensatory postural adjustments, including scoliosis. However, this association is usually multi-factorial, bidirectional, and varies among individuals.

[0007] Currently, clinical screening mainly relies on X-ray examinations and professional physician diagnoses, but there are problems such as cumbersome operations and low efficiency. According to statistics, in large-scale campus screening activities, a few doctors need to complete the screening of a large number of students within a few hours, and the traditional single-disease screening often ignores the associations between diseases, affecting the diagnostic accuracy. ( Figure 16 For the existing complete screening process)

[0008] The development of IMU technology provides a new technical solution to solve the above problems. The IMU integrates an accelerometer, a gyroscope, and a magnetometer, and can simultaneously measure the acceleration, angular velocity, and direction information of each segment of the human body, with technical advantages such as high sampling frequency and multiple measurement dimensions. By systematically arranging multiple IMU sensors, synchronous acquisition of the motion characteristics of the human torso and lower limbs can be achieved, thereby completing the unified screening of multiple diseases. This solution is not only non-invasive and portable for large-scale population screening, but also can obtain quantitative kinematic parameters, and by analyzing the overall motion characteristics of the human body, better grasp the associations between diseases and improve the accuracy and efficiency of screening.

[0009] Adolescent Idiopathic Scoliosis (AIS) is the most common spinal deformity among adolescents aged 10 to 18, with an incidence rate of 1.5% - 3%. The ratio of female to male patients is approximately 8:1. AIS patients often exhibit three-dimensional spinal deformities, postural asymmetries, vertebral and thoracic cage deformities, etc., and these structural abnormalities further lead to functional abnormalities such as proprioceptor dysfunction and motor balance in patients.

[0010] Clinical studies have shown that AIS patients have significant gait abnormalities, mainly manifested as characteristics such as slowed walking speed, disordered gait cycles, and asymmetry of the gait cycles of the left and right feet. These gait changes are closely correlated with the degree of scoliosis. Even after considering factors such as gender and weight, scoliosis remains the main factor affecting the walking performance of patients. Therefore, precise gait analysis of AIS patients not only helps in early diagnosis and disease assessment, but also provides an objective basis for the formulation and efficacy evaluation of rehabilitation treatment plans.

[0011] Currently, the commonly used gait analysis techniques in clinical practice mainly include three types: optoelectronic systems, pressure insoles, and inertial navigation systems. Although optoelectronic systems can provide fast and accurate acquisition of physical movements and offer multi-dimensional measurement data, the equipment cost is high, and they require a professional laboratory environment and a large amount of space, making it difficult to meet the needs of clinical popularization. The pressure insole system has the advantages of being easy to use and suitable for various foot sizes, but additional limb data is needed to fully analyze gait, and the measurement effect is poor on uneven roads. In contrast, inertial navigation systems have significant advantages such as being convenient to use and carry, small in size, light in weight, cost-effective, and capable of monitoring gait characteristics during daily activities, making them more suitable for clinical promotion and application.

[0012] However, the existing gait analysis systems based on inertial measurement units (IMUs) still have serious deficiencies in terms of technical implementation and clinical application. First, the data acquisition architecture design is unreasonable. Most systems adopt a scheme of using a single controller to uniformly collect data, which not only has low sampling efficiency but also causes the loss of all system data once a failure occurs. Due to the lack of an effective fault detection and location mechanism, it is difficult for operators to discover and handle data acquisition anomalies in a timely manner.

[0013] Second, the distribution scheme of sensors lacks systematic consideration. For example, in solutions such as the patent "Wearable Lower Limb Posture Tracking" and "Motion Injury Population Based on Wearable Devices", only a small number of sensors are configured on the lower limbs, ignoring the integrity of human movement. There are no sensors set on the upper torso, unable to capture trunk compensation, and there is also a lack of a unified motion reference coordinate system, seriously affecting the accuracy and integrity of gait analysis.

[0014] Third, the wearable structure design of existing devices is rough. Most systems adopt a simple strap fixation method, such as the simple fixation scheme using only two IMU sensors in "A Wearable Device", which can neither ensure the stability of the sensor position nor facilitate quick wearing. Especially in clinical applications, due to the lack of consideration for patients with different body types, the versatility and usability of the device are poor.

[0015] Fourth, the hardware integration level is not high. For example, the patent "Gait Analysis Based on Camera and Inertial Navigation" requires the simultaneous configuration of a camera and marker points, the system structure is complex, and repeated calibration is required during the use operation process. In addition, when multiple sets of devices are worn on the patient at the same time, the patient's freedom of movement is easily restricted by the experimental instruments, resulting in the inability to truly restore the real gait of the collected gait data.

[0016] These technical problems severely restrict the popularization and application of gait analysis in the clinical diagnosis and treatment of AIS. Therefore, there is an urgent need to develop a gait analysis system that combines portability, high precision, and clinical practicability to meet the growing needs in the field of medical rehabilitation.

[0017] Existing gait analysis systems have obvious technical limitations. Although optical motion capture systems can provide high-precision kinematic data, the equipment cost is extremely high, often reaching hundreds of thousands of yuan, and they require a professional laboratory environment and a large amount of space, making it difficult to meet the needs of clinical popularization applications. Although pressure measurement systems can provide ground reaction force data, the measurement accuracy significantly decreases on outdoor uneven roads, and single plantar pressure data cannot comprehensively reflect human movement characteristics. Additional motion sensors need to be configured to obtain a complete gait analysis result.

[0018] Existing inertial measurement unit (IMU) systems, although having the advantages of good portability and low cost, still have the following problems in practical applications: First, the sensor quantity and distribution scheme lack systematic consideration. Most systems only configure a small number of sensors on the lower limbs, ignoring the integrity of human movement and the compensation mechanism between segments, resulting in incomplete data acquisition; Second, existing systems often focus on optimizing a single technical indicator and lack an overall solution from hardware design to data acquisition, resulting in insufficient system stability and reliability; Third, the applicability of existing devices in actual application scenarios is insufficiently considered. For example, the sensor fixing method is simple, the data transmission cable is exposed, and there is a lack of a fault warning mechanism. These problems seriously affect the actual use effect of the device in the clinical environment. Summary of the Invention

[0019] In view of the above defects of the prior art, the present invention provides an innovative portable gait analysis system. This system not only adopts an innovative nine-point scheme in sensor distribution but also forms a complete technical solution through collaborative design at multiple technical levels such as PCB modular design, power management optimization, and data transmission protection. The system innovatively designs a backpack-style integrated wearable structure and fully considers the actual needs of clinical application scenarios on this basis: The FFC flexible cable is used in combination with a protective tube design to avoid data transmission interference and potential safety hazards in use; Through real-time LED status indication and multiple data protection mechanisms, operators can promptly discover and handle abnormal situations. The total cost of this system does not exceed one-tenth of that of ordinary optical systems and can be used in any scenario, providing a feasible solution for the popularization of clinical gait analysis applications.

[0020] The objective of the present invention is to develop a portable gait analysis system with high cost performance, easy operation, and high reliability, so as to achieve accurate measurement and comprehensive analysis of human motion characteristics. The specific objectives include: First, through an optimized sensor distribution scheme, more comprehensive kinematic data can be obtained; Second, through systematic hardware design and reliable data protection mechanisms, the stable operation of the device in a clinical environment can be ensured; Third, through user-friendly interaction design and perfect protection measures, the usability of the system in practical applications can be improved; Fourth, through modular design and cost control, the clinical popularization and application of gait analysis technology can be promoted.

[0021] To achieve the above technical objectives, the present invention provides:

[0022] A portable gait analysis system based on inertial sensors, characterized in that it includes an IMU sensor array composed of nine inertial measurement units and a distributed data acquisition module; wherein:

[0023] The first inertial measurement unit, the second inertial measurement unit, and the third inertial measurement unit are used to be fixed on the upper torso area;

[0024] The fourth inertial measurement unit, the fifth inertial measurement unit, and the sixth inertial measurement unit are used to be fixed on the left lower limb;

[0025] The seventh inertial measurement unit, the eighth inertial measurement unit, and the ninth inertial measurement unit are used to be fixed on the right lower limb;

[0026] The distributed data acquisition module includes three independent acquisition units, which are respectively connected to the inertial measurement units on the upper torso, the left lower limb, and the right lower limb and collect corresponding data, realizing partitioned data acquisition and storage;

[0027] Each of the inertial measurement units and the independent acquisition units is fixed on the user's body through an integrated wearable structure.

[0028] A further improvement of the present invention lies in that the fixed positions of the inertial measurement units of the IMU sensor array are respectively:

[0029] The fixed positions of the first inertial measurement unit and the second inertial measurement unit are at the left and right scapulas respectively, for detecting the stability index of the upper limb and the symmetry characteristics of the left and right sides during walking; the fixed position of the third inertial measurement unit is at the sacral position, serving as the reference point of the entire monitoring system;

[0030] The fixed positions of the fourth inertial measurement unit and the seventh inertial measurement unit are respectively at the outer sides of the middle segments of the left and right femoral shafts, for detecting the motion characteristics of the thigh segment;

[0031] The fixed positions of the fifth inertial measurement unit and the eighth inertial measurement unit are respectively at the outer sides of the middle segments of the left and right tibias, for detecting the motion parameters of the calf segment;

[0032] The fixed positions of the sixth inertial measurement unit and the ninth inertial measurement unit are respectively the dorsal sides of the proximal ends of the second metatarsal bones on the left and right sides, and are used to detect the kinematic changes of the foot during the stance phase and the swing phase.

[0033] A further improvement of the present invention is that each of the independent acquisition units is provided with a memory card for storing data;

[0034] Each of the independent acquisition units collects data frames from the inertial measurement unit connected thereto at a predetermined frequency; the data frames include timestamp, acceleration, angular velocity, and attitude angle information;

[0035] Each independent acquisition unit is correspondingly configured with an LED status indicator for real-time feedback of abnormal data storage;

[0036] The sampling frequency of the independent acquisition unit is set to 50 Hz.

[0037] A further improvement of the present invention is that the control logic of the LED status indicator is: it remains constantly on when the memory card is written normally; it immediately goes out when it is detected that the memory card is not inserted or the writing fails, triggering an operation interruption.

[0038] A further improvement of the present invention is that each of the independent acquisition units connects the corresponding inertial measurement units in sequence through an FFC flexible cable; an opening self-rolling textile wire harness protection tube is sleeved outside the FFC cable.

[0039] A further improvement of the present invention is that the integrated wearable structure includes a backpack-type upper torso fixing device and a lower limb rehabilitation bandage assembly;

[0040] Three of the independent acquisition units are integrated on the same PCB board as the main circuit board;

[0041] The main circuit board, the power module, and the third inertial measurement unit are integrated on the backpack-type upper torso fixing device; the first inertial measurement unit and the second inertial measurement unit are fixed on the two straps of the backpack-type upper torso fixing device;

[0042] The lower limb bandage assembly fixes the inertial measurement units of the lower limbs through quick-release buckles and a margin adjustment structure.

[0043] A further improvement of the present invention is that it further includes a clinical analysis system, and the analysis process includes:

[0044] A data import module for reading data from each memory card respectively;

[0045] A preprocessing module for performing time alignment, interpolation, and digital noise reduction processing on the read data;

[0046] The kinematic analysis module calculates the flexion / extension, abduction / adduction, and internal / external rotation degree-of-freedom parameters of the hip, knee, and ankle joints in layers based on the preprocessed data.

[0047] The report generation module automatically outputs a standardized report containing range of motion analysis (ROM), symmetry coefficient, and anomaly markers.

[0048] The technical solution provided by the present invention has the following technical effects:

[0049] The present invention adopts a scheme of three independent acquisition units for zonal acquisition, and each independent acquisition unit is responsible for the data acquisition task of a specific area. This design not only improves the sampling efficiency, but more importantly, realizes the zonal storage and protection of data. Through the real-time feedback mechanism of the LED indicator lights, the system can timely detect and locate the fault area. Even if a single acquisition module has problems, the data in other areas is still available, which significantly improves the system reliability.

[0050] The second is the nine-point sensor distribution scheme. Based on the principles of human biomechanics, this scheme arranges sensors at the key nodes of human movement: the left and right scapulas and the sacrum position of the upper torso, as well as the thighs, calves, and feet of the lower limbs. This distribution scheme can not only comprehensively capture the human movement characteristics, but also establish a unified reference coordinate system through the reference sensor at the sacrum, providing a reliable basis for subsequent kinematic analysis.

[0051] The third is the integrated wearable structure design. The present invention integrates the sensors and control modules of the upper torso through a backpack design, and uses professional rehabilitation bandages combined with quick-release buckles to fix the lower limb sensors. This design not only ensures the stability of the sensor positions, but also greatly improves the wearing convenience. Especially the mother-child sticker and connection buckle adjustment structure at the shoulder strap, as well as the allowance design of the bandage, enable the system to adapt to users with different body types.

[0052] The fourth is the modular hardware design. The system adopts a four-level PCB structure and achieves high integration through reasonable function division and layout. The main circuit board integrates the core processing unit and the data storage module, and the secondary circuit board and the terminal circuit board achieve reliable transmission of sensor signals through an optimized wiring scheme. Especially the design of using an open self-rolling textile wire harness protection tube outside the FFC cable not only solves the electromagnetic interference problem, but also avoids potential safety hazards during use.

[0053] The following will further illustrate the concept, specific structure, and technical effects of the present invention with reference to the accompanying drawings to fully understand the purpose, features, and effects of the present invention. Description of the Drawings

[0054] Figure 1 It is the overall schematic diagram of the sensor distribution of the portable gait analysis system based on inertial sensors of the present invention;

[0055] Figure 2 It is the system hardware architecture and data flow diagram;

[0056] Figure 3 It is the schematic diagram of the four - level structure and connection of the PCB;

[0057] Figure 4 They are the perspective view, front view and rear view of the portable gait analysis system based on inertial sensors of the present invention;

[0058] Figure 5 It is the schematic diagram of the housing of the waist main controller;

[0059] Figure 6 It is Figure 4 the schematic diagram of the shoulder telescopic belt structure in

[0060] Figure 7 It is Figure 4 the schematic diagram of the front waist snap structure in

[0061] Figure 8 It is the schematic diagram of the housing structure of the secondary PCB board;

[0062] Figure 9 It is the schematic diagram of the housing structure of the fourth - level PCB board;

[0063] Figure 10 It is the schematic diagram of the housing and connection structure of the lower - limb IMU;

[0064] Figure 11 It is the schematic diagram of the operation process and feedback signal;

[0065] Figure 12 It is the flow chart of scoliosis screening;

[0066] Figure 13 It is the GUI interface of the screening device clinical analysis system;

[0067] Figure 14 It is the GUI interface of the data import module;

[0068] Figure 15 It is the GUI interface of the data processing module;

[0069] Figure 16 It is the GUI interface of the motion analysis module;

[0070] Figure 17 It is the GUI interface of the report generation module. Detailed implementation manners

[0071] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0072] As Figure 1 shown, an embodiment of the present invention provides a portable gait analysis system based on inertial sensors. The system of the present invention adopts a nine-point sensor distribution scheme and designs a systematic monitoring scheme based on the principles of human movement biomechanics. During the gait cycle, there are obvious motion compensation mechanisms and synergistic effects between the joints and limb segments of the human body. To comprehensively capture these characteristics, nine IMU sensors (inertial measurement units) are arranged at the key motion nodes of the upper torso and both lower limbs, realizing the accurate acquisition of human movement characteristics. (See Figure 1 ).

[0073] Hereinafter, the nine measurement units, namely the first inertial measurement unit, the second inertial measurement unit, the third inertial measurement unit, the fourth inertial measurement unit, the fifth inertial measurement unit, the sixth inertial measurement unit, the seventh inertial measurement unit, the eighth inertial measurement unit, and the ninth inertial measurement unit, are respectively referred to as IMU1, IMU2, IMU3, IMU4, IMU5, IMU6, IMU7, IMU8, and IMU9.

[0074] In the upper torso part, the system sets three monitoring points: IMU1 and IMU2 are respectively located at the left and right scapulae. By monitoring the movement trajectories and posture changes of the scapulae, the stability index of the upper limb and the symmetry characteristics of the left and right sides during walking are analyzed; IMU3 is fixed at the pelvic position (sacral position), which is closest to the center of gravity of the human body and can be used as a reference point for the entire monitoring system to establish an overall coordinate system for human movement and realize the unified analysis of the movement parameters of each segment.

[0075] In the lower limb part, the system adopts a symmetric layout scheme: IMU4, IMU5, and IMU6 are arranged in sequence on the left lower limb, and IMU7, IMU8, and IMU9 are arranged in sequence on the right lower limb. Among them, IMU4 and IMU7 are fixed on the outer sides of the middle segments of the left and right femoral shafts, where the influence of muscle contraction on the sensors can be minimized to accurately reflect the movement characteristics of the thigh segment; IMU5 and IMU8 are located on the outer sides of the middle segments of the left and right tibias, where the bony landmarks are obvious and the fixing effect is good, enabling the stable acquisition of the movement parameters of the calf segment; IMU6 and IMU9 are installed on the dorsal sides of the proximal ends of the second metatarsals on the left and right sides, and the kinematic changes of the foot during the stance phase and swing phase can be accurately obtained by monitoring here.

[0076] The system adopts a unified spatial coordinate definition scheme: the Z-axis of each IMU sensor is adjusted to be vertically upward and parallel to the gravity direction, serving as the reference axis for attitude calculation; the X-axis points in the forward direction of the human body and is used to calculate walking acceleration and speed parameters; the Y-axis remains horizontal and perpendicular to the motion plane and is used to analyze lateral balance characteristics. The system designs a dual calibration mechanism: first, through the built-in automatic calibration program, an initial attitude matrix is established using gravitational acceleration and geomagnetic field data; second, during actual wearing, by precisely aligning the sensor directions, the accuracy of the initial pose is ensured, thereby improving the reliability of subsequent motion parameter calculations.

[0077] This invention uses three single-chip microcomputers to implement three independent acquisition units for distributed data acquisition. Each independent acquisition unit corresponds to three IMU sensors, and synchronous monitoring of multi-point motion parameters is achieved through a task partition acquisition strategy. The determination of the system sampling frequency is based on the analysis of human motion characteristic frequencies: Fourier transform is used to perform spectral analysis on the motion data, and at the same time, the Lomb-Scargle periodogram method is used for verification. The results show that the main frequency components of human motion characteristics are all within 25 Hz. According to the sampling theorem, the system sampling frequency is set to 50 Hz to ensure that the acquired data can completely restore human motion characteristics.

[0078] The specific partition acquisition scheme of the system is as follows: the first independent acquisition unit is responsible for data acquisition in the upper torso area, connecting IMU1 and IMU2 at the left and right scapulas and IMU3 at the pelvis, and mainly acquires data on torso attitude changes; the second independent acquisition unit is responsible for data acquisition in the left lower limb, connecting IMU4 at the left thigh, IMU5 at the left calf, and IMU6 at the left instep, and monitors the motion parameters of the left lower limb; the third independent acquisition unit is responsible for data acquisition in the right lower limb, connecting IMU7 at the right thigh, IMU8 at the right calf, and IMU9 at the right instep, and monitors the motion parameters of the right lower limb. Adopting the partition acquisition strategy can effectively reduce the data processing load of a single processing unit and improve the overall sampling efficiency of the system. (See Figure 2 )

[0079] In terms of data storage, the system configures an independent 32GB SD memory card for each independent acquisition unit. The SD card is formatted with the FAT32 file system, and the data is stored in binary format. Each data frame contains timestamp, acceleration, angular velocity, and attitude angle data. The system designs a real-time data monitoring mechanism: three LED indicators are configured to correspond to the data storage status of the three independent acquisition units respectively. When data is written to the SD card normally, the corresponding LED light remains on constantly; if abnormal data writing is detected, such as the SD card not being inserted, writing failure, etc., the corresponding LED light will go out immediately, prompting the operator to terminate the test in time and troubleshoot the fault. This design can effectively avoid data loss and ensure the integrity of the test data.

[0080] As Figure 3 shown, in this embodiment, a four-level PCB design is adopted to improve the system integration and stability. The three independent acquisition units are integrated on the same PCB board, serving as the main circuit board PCB1. PCB1 adopts a double-sided design with a size of 120×120mm.

[0081] On the top layer of the main circuit board PCB1, 3 SD card slots, 1 tactile button, and 3 LED indicators are arranged; on the bottom layer, 3 single-chip microcomputers and an IMU sensor are arranged as the third inertial measurement unit, and 4 FPC interfaces for connecting PCB2 and PCB4 are set. The power management circuit adopts an AMS1117-3.3 linear voltage regulator. A 10μF and a 100μF capacitor are connected in parallel at the input end of the voltage regulator for high-frequency and low-frequency noise filtering, and a 10μF and a 100μF capacitor are also connected in parallel at the output end to stabilize the output voltage, ensuring the power supply quality of the sensor. The tactile button on the main circuit board PCB1 is connected to the single-chip microcomputers of the 3 independent acquisition units. When the tactile button is triggered, the 3 single-chip microcomputers start collecting data synchronously. (See Figure 4 )

[0082] The secondary circuit boards PCB2 and PCB3 adopt a double-layer design with a size of 60×60mm each. On the bottom layer, IMU sensors and their supporting circuits are arranged, including decoupling capacitors, pull-up resistors, etc.; on the top layer, FPC connectors are arranged to realize signal interconnection with adjacent PCB boards. The PCB design adopts a double-layer structure: the top layer and the bottom layer are each used for signal routing, and vias are used to conduct the wires that need to be connected. This design can effectively reduce signal interference and improve data transmission quality. (See Figure 5 、 Figure 6 ). The fourth inertial measurement unit and the seventh inertial measurement unit are respectively mounted on two secondary circuit boards PCB2; the fifth inertial measurement unit and the eighth inertial measurement unit are respectively mounted on the secondary circuit board PCB3.

[0083] The ultimate circuit board PCB4 adopts a single-layer design with a size of 18×26 mm. Only the IMU sensor and the FPC connector are arranged on the top layer. The single-layer design can reduce the weight of the sensor and minimize the impact on human movement. The first inertial measurement unit, the second inertial measurement unit, the sixth inertial measurement unit, and the ninth inertial measurement unit are respectively mounted on an ultimate circuit board PCB4.

[0084] The PCB boards are connected by FFC flexible flat cables of different specifications: an 11P, 0.5 mm pitch FFC is used between PCB1 and PCB2, a 9P, 0.5 mm pitch FFC is used between PCB2 and PCB3, and a 4P, 0.5 mm pitch FFC is used between PCB3 and PCB4. The flexible flat cables adopt a same-direction design, which simplifies the PCB wiring difficulty.

[0085] The specific structure of the waist master controller 5 is as Figure 5 shown, including the upper shell 52 and the lower shell 55 of the main circuit board PCB1 of the power module 14; a bandage connection buckle 53 is provided at the edge of the lower shell 55, and a limit hole 54 is also provided on the upper shell 52.

[0086] The shell structure of the secondary PCB board is as Figure 8 shown, including the upper shell 102 and the lower shell 105; the lower shell 105 is provided with a bandage connection buckle 103 and an FFC connection hole 104; a limit hole 101 is opened on the upper shell 102.

[0087] The schematic diagram of the shell structure of the fourth-level PCB board is as Figure 9 shown, including the upper shell 201 and the lower shell 202; a bandage connection buckle 203 is opened on the lower shell 202, an FFC connection hole is opened on one side of the upper shell 201, and a limit hole 204 is also provided on the upper shell 201 for setting screws to fix the upper shell 201 and the lower shell 202.

[0088] The system is powered by a 5V / 3A mobile power supply input through a Type-C interface. After calculation, the working current of a single IMU sensor is about 30 mA, the working current of the single-chip microcomputer is about 50 mA, the peak write current of the SD card is about 50 mA, and the currents of the LED and the button can be ignored. The total current consumption of the system is about 600 mA. Selecting a power supply scheme with a rated power of 22.5 W can ensure the stable operation of the system and have sufficient power margin to cope with high-load situations such as sudden data writing.

[0089] The integrated wearable structure of the present invention adopts a backpack-type integrated design and realizes quick wearing and precise positioning through structural optimization (see Figure 4)。In the upper torso part, an improved backpack structure is designed as a backpack-type upper torso fixing device. Among them, IMU1 and IMU2 are fixed on the inner side of the straps at the left and right scapulas, and PCB1 and its supporting control components, IMU3 and the power bank are integrated at the back shell. When in use, the operator only needs to put the backpack straps over the shoulders and fasten the buckle in front of the waist to complete the wearing of the upper torso part. To meet the needs of users with different body types, a mother-and-son sticker and a connection buckle adjustment structure are set at the straps near the scapulas, and the adjustment range can reach 5-8 cm, ensuring that the IMU sensor can stably fit the human body surface and improving the measurement accuracy.

[0090] (See Figures 5 - 8 ).

[0091] As Figure 4 shown, Figure 4 are the three-dimensional view, front view and rear view of the portable gait analysis system based on inertial sensors of the present invention; Figure 4 In it, the first inertial measurement unit 1 and the second inertial measurement unit 13 are installed on the strap 2. The third inertial measurement unit 15 and the waist main controller 5 are integrated together; the main circuit board PCB1 and the power module 14 are also integrated in the waist main controller 5; the waist main controller 5 is fixed on the waist through the waist stretch strap 4 and the waist front buckle 3. The FFC protection tube 6 extended from the waist main controller 5 is connected to the circuit of the lower limb part, including the fourth inertial measurement unit 7 and the seventh inertial measurement unit 16. The fourth inertial measurement unit 7 and the seventh inertial measurement unit 16 are fixed at the predetermined positions on the legs through the thigh stretch strap; the fifth inertial measurement unit 9 and the eighth inertial measurement unit 17 are fixed at the predetermined positions through the calf stretch strap 10; the sixth inertial measurement unit 11 and the ninth inertial measurement unit 18 are fixed at the predetermined positions through the foot stretch strap 12.

[0092] In the lower limb part, the present invention adopts a professional sports rehabilitation bandage and a fixing scheme with a buckle. The used bandage has an adjustment margin of 5-10 cm, which can meet the size requirements of users with different body types. Each IMU sensor is assembled in a customized square protective shell, and the shell is firmly connected to the internal PCB board and the IMU sensor through two M2.5 specification mounting holes. When in use, pass the bandage through the shell equipped with the IMU sensor and fix it with the buckles at both ends of the bandage. The tightness can be flexibly adjusted according to the limb circumference of the user, ensuring that the sensor closely adheres to the human skin and minimizing the influence of skin and soft tissue deformation on the measurement data.

[0093] (See Figure 9 , Figure 10 , Figure 11 ).

[0094] The signal connections between the IMU sensor units of the system are realized by using FFC cables of different specifications. To improve the reliability of the system, each FFC cable is externally sleeved with an open self-rolling textile wire harness protection tube, which can not only effectively shield external electromagnetic interference, but also prevent the cable from being damaged or tangled during the test, and at the same time reduce the safety hazard of users being tripped by the cable.

[0095] The specific operation process is as follows: First, complete the wearing of the upper torso device, including passing both arms through the backpack shoulder straps and buckling the front chest fixing buckle, and adjusting the shoulder straps to make IMU1 and IMU2 stably fit the left and right scapulas. Subsequently, install the lower limb sensors in turn, including the IMU sensors on the left and right thighs, calves, and insteps. The selection of the sensor installation position is crucial for subsequent data analysis: the thigh sensor should be located on the outer side of the middle segment of the femoral shaft, the calf sensor should be located on the outer side of the middle segment of the tibia, and the instep sensor should be located on the dorsal side of the proximal end of the second metatarsal bone. After installation, it is necessary to carefully adjust the position and direction of each sensor: the shell should be parallel to the bony landmark points of the corresponding part, and the front of the sensor (the side with the nut) should face forward, and the deviation angle should be controlled within ±5°.

[0096] The operation steps for system power supply and data acquisition are as follows: After completing the sensor position calibration, connect the Type-C interface of the power bank to the system power supply interface. After the system is powered on, first keep it in a stationary state for 5 seconds to allow each sensor to complete initialization. When collecting data, press the touch button for the first time to start recording, and the corresponding LED indicator lights up. At this time, the operator can start walking; after the test is completed, when the operator stops walking and remains in a stationary state, press the touch button again to end this recording, and the LED indicator goes out accordingly.

[0097] This embodiment also includes a clinical analysis system, which realizes the full-process automatic processing from data collection to analysis result output. The system adopts a modular design concept and mainly includes a data import module, a data preprocessing module, a kinematic analysis module, and a report generation module. (See Figure 12 、 Figure 13 )

[0098] 1. Data import module (see Figure 14 )

[0099] The system is designed with three independent data import interfaces, which respectively correspond to the SD card data reading of the left sensor group, the upper sensor group, and the right sensor group. The original data of each sensor group includes timestamp, device identification, three-axis acceleration, three-axis angular velocity, and quaternion attitude information. After the data import is completed, the system automatically displays the import status prompt on the interface.

[0100] 2. Data preprocessing module (see Figure 15 )

[0101] This module first performs automated preprocessing on the raw data of nine sensors, mainly including:

[0102] - Time series alignment: Based on the timestamp information, unify the data of different sensors onto the same time axis

[0103] - Data interpolation processing: Interpolate and supplement possible data missing points to ensure data continuity

[0104] - Signal denoising: Use digital filtering algorithms to eliminate high-frequency noise and improve signal quality

[0105] The preprocessed data is previewed in real time in tabular form on the interface, facilitating the operator to confirm the data quality.

[0106] 3. Kinematic analysis module (see Figure 16 )

[0107] Adopt a hierarchical analysis structure to conduct specialized kinematic analyses for the hip joint, knee joint, and ankle joint respectively:

[0108] (1) Joint motion analysis

[0109] - Different joints can be selected for analysis through the drop-down menu at the top of the interface

[0110] - Calculate the motion parameters of three degrees of freedom, namely flexion / extension, abduction / adduction, and internal / external rotation, for each joint respectively

[0111] - Automatically extract 5 stable gait cycles as analysis samples

[0112] (2) Motion feature quantification

[0113] Conduct multi-dimensional analysis on the extracted gait cycles:

[0114] - ROM (Range of Motion) analysis: Calculate the range of motion of each joint in different motion directions

[0115] - Correlation analysis: Evaluate the coordination of the motion of the same-named joints on the left and right sides

[0116] - Symmetry analysis: Quantify the deviation degree of the motion of the joints on the left and right sides

[0117] - RMSE (Root Mean Square Error) analysis: Evaluate the volatility of the motion curve

[0118] 4. Report generation module (see Figure 17 )

[0119] The system automatically integrates the analysis results to generate a standardized clinical analysis report. The report content includes:

[0120] - Basic information: Subject information, test time, analysis parameters, etc.

[0121] - Movement curves: Movement trajectory diagrams of each joint, highlighting the left - right comparison

[0122] - Quantitative indicators: Core parameters such as range of motion, symmetry coefficient, etc.

[0123] - Abnormality alerts: Special markings for indicators beyond the normal range

[0124] The design features of this system are as follows: First, it realizes full automation of data processing, reducing the operation difficulty; second, it adopts a multi - dimensional analysis method to provide a comprehensive kinematic assessment; third, it has a standardized report output, facilitating doctors' rapid clinical diagnosis.

[0125] In terms of the data acquisition architecture, the present invention innovatively adopts a scheme of three MCUs for partitioned acquisition. Each MCU is responsible for the data acquisition task of a specific area, which not only improves the sampling efficiency but also realizes rapid fault location through the real - time feedback mechanism of LED indicators. This distributed architecture ensures that even when a single acquisition module has problems, the data in other areas is still available, significantly superior to the problem in the prior art where a single controller is prone to cause the loss of the overall system data.

[0126] In the sensor layout scheme, based on the principle of human biomechanics, the present invention innovatively proposes a nine - point sensor distribution scheme, arranging sensors at the key nodes of human movement. This scheme can not only comprehensively capture human movement characteristics but also establish a unified reference coordinate system through the reference sensor at the sacrum. Compared with the prior art scheme of only configuring a small number of sensors in the lower limbs, the present invention can more accurately reflect the integrity and coordination of human movement.

[0127] In the design of the wearable structure, the present invention integrates the upper torso sensors and the control module through a backpack - type design, and uses professional rehabilitation bandages combined with quick - release buckles to fix the lower limb sensors. In particular, the mother - son sticker and connection buckle adjustment structure at the shoulder strap, as well as the surplus design of the bandage, enable the system to adapt to users of different body types. This is much superior to the limitations of the simple strap - fixing method in clinical applications in the prior art.

[0128] In terms of hardware integration, the present invention adopts a modular design with a four - level PCB structure, achieving high integration through reasonable function division and layout. In particular, the design of using an open - ended self - rolling textile wire harness protection tube outside the FFC cable solves both the electromagnetic interference problem and avoids potential safety hazards during use. This is significantly superior to the prior art design with a complex structure, difficult maintenance, and potential safety hazards.

[0129] The above embodiments are only illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A portable gait analysis system based on inertial sensors, characterized in that: It includes an IMU sensor array consisting of nine inertial measurement units and a distributed data acquisition module; among which: The first inertial measurement unit, the second inertial measurement unit, and the third inertial measurement unit are used to be fixed in the upper torso area; The fourth inertial measurement unit, the fifth inertial measurement unit, and the sixth inertial measurement unit are used to be fixed on the left lower limb; The seventh inertial measurement unit, the eighth inertial measurement unit, and the ninth inertial measurement unit are used to be fixed on the right lower limb; The distributed data acquisition module consists of three independent acquisition units, which are respectively connected to the inertial measurement units of the upper torso, left lower limb and right lower limb and collect corresponding data to realize partitioned data acquisition and storage; Each of the inertial measurement units and the independent acquisition unit is fixed on the user's body through an integrated wearable structure.

2. The portable gait analysis system based on inertial sensors according to claim 1, characterized in that: The fixed positions of each inertial measurement unit of the IMU sensor array are: The first inertial measurement unit and the second inertial measurement unit are fixed at the left and right shoulder blades, respectively, to detect the stability index of the upper limbs and the symmetry characteristics of the left and right sides during walking; The fixed position of the third inertial measurement unit is the sacrum position, which serves as the reference point of the entire monitoring system; The fourth inertial measurement unit and the seventh inertial measurement unit are fixed at the outer sides of the middle sections of the left and right femoral shafts, respectively, to detect the movement characteristics of the thigh segments; The fifth inertial measurement unit and the eighth inertial measurement unit are fixed at the outer sides of the middle sections of the left and right tibias, respectively, and are used to detect the motion parameters of the calf sections; The sixth inertial measurement unit and the ninth inertial measurement unit are fixed at the dorsal side of the proximal end of the second metatarsal on the left and right sides, respectively, and are used to detect the kinematic changes of the foot in the stance phase and the swing phase.

3. The portable gait analysis system based on inertial sensors according to claim 1, characterized in that: Each of the independent acquisition units is provided with a memory card for storing data; Each of the independent acquisition units acquires data frames from the inertial measurement unit connected thereto at a predetermined frequency; the data frames include timestamp, acceleration, angular velocity and attitude angle information; Each independent acquisition unit is equipped with an LED status indicator to provide real-time feedback on data storage anomalies; The sampling frequency of the independent acquisition unit is set to 50 Hz.

4. The portable gait analysis system based on inertial sensors according to claim 3 is characterized in that: The control logic of the LED status indicator light is: it remains on when the storage card is written normally; it turns off immediately when it is detected that the storage card is not inserted or the writing fails, triggering an operation interruption.

5. The portable gait analysis system based on inertial sensors according to claim 3, characterized in that: Each of the independent acquisition units is sequentially connected to the corresponding inertial measurement unit via an FFC flexible cable; the outside of the FFC cable is covered with an open self-winding textile harness protection tube.

6. The portable gait analysis system based on inertial sensors according to claim 1, characterized in that: The integrated wearable structure includes a backpack-type upper torso fixation device and a lower limb rehabilitation bandage assembly; The three independent acquisition units are integrated on the same PCB board as a main circuit board; The main circuit board, the power module and the third inertial measurement unit are integrated on the backpack-type upper torso fixing device; the first inertial measurement unit and the second inertial measurement unit are fixed on two straps of the backpack-type upper torso fixing device; The lower limb bandage assembly fixes each inertial measurement unit of the lower limb through a quick buckle and a margin adjustment structure.

7. The portable gait analysis system based on inertial sensors according to claim 1, characterized in that: It also includes a clinical analysis system, and the analysis process includes: A data import module is used to read data from each storage card respectively; A preprocessing module is used to perform time alignment, interpolation and digital noise reduction on the read data; The kinematic analysis module calculates the freedom parameters of hip, knee and ankle joint flexion and extension, internal and external abduction, and internal and external rotation in layers based on the preprocessed data; The report generation module automatically outputs standardized reports including range of motion analysis ROM, symmetry coefficients and abnormality marks.

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