Fall prevention device for sensing position sensation and motion sensation of human joints based on brain-computer fusion and control method

Abstract

The invention belongs to the technical field of anti-tumble devices, and discloses a tumble prevention device for sensing human joint position sensation and motion sensation based on brain-computer fusion, which comprises a brain-computer fusion sensing interface, an intelligent knee pad, a wearable system, a balance module, a support module and a control module, the signal is transmitted to sensory nerves through an electrode implanted into the brain, so that the sensory function is reconstructed; the mode of electromyographic signal detection and rigid structure supporting is adopted, the feature electromyographic signals before falling are collected, the mechanical supporting device is automatically triggered, supporting is guaranteed to be safe, detection and processing of the electromyographic signals of specific muscle groups before falling are achieved, and the safety of falling is improved. And the whole process of rigid support protection, alarm and sending positioning on the human body during falling is covered.

Description

Technical Field

[0001] The present invention belongs to the technical field of anti-fall devices, and in particular relates to a fall prevention device and a control method based on brain-machine fusion perception of human joint position and motion. Background Art

[0002] my country has entered a deeply aging society, and people are paying more and more attention to the health problems of the elderly. Falling is the most serious challenge currently faced by the elderly. Due to the weakened proprioception of the elderly, it is difficult to take timely and effective preventive actions when a fall occurs. According to incomplete statistics, the proportion of elderly people in my country who are hospitalized due to falls is 5 times that of hospitalization due to other accidents. Many elderly people often suffer from physical, living and psychological obstacles after falling, which increases the family and socioeconomic burden. At present, there are few smart products for preventing falls for the elderly on the market. Most of them alarm by detecting the electromyographic signals during the fall or send information such as the fall location to relatives after the fall, and often lack protective devices for the human body during falls. The existing mechanical structure protective device forms a fixed support state after the contact limit, and has problems such as large size, inconvenience in wearing, and long detection time, which limit its use.

[0003] Through the above analysis, the problems and defects of the existing technology are as follows: There are few smart products for preventing the elderly from falling on the market. Most of them alarm by detecting the electromyographic signal when falling or send information such as the fall location to relatives after falling, and often lack protective devices for the human body when falling. The existing mechanical protective devices form a fixed support state after contacting the limit position, and have problems such as large size, inconvenience in wearing, and long detection time, which limit their use. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a fall prevention device based on brain-machine fusion perception of human joint position and movement.

[0005] The present invention is implemented as follows: a fall prevention device based on brain-machine fusion perception of human joint position and motion sense comprises:

[0006] Smart knee pads, wearable systems, balance modules, support modules, control modules;

[0007] The smart kneepad is placed at the knee joint of a human body, and is configured to detect and process characteristic muscle electromyographic signals during a fall. The wearable system is connected to the waist, buttocks, and thighs of the human body, and the balance module is placed outside the hip joint of the human body;

[0008] The balancing module is connected to the wearable system, and the balancing module is configured to always keep the supporting module perpendicular to the ground and not interfere with the normal movement of the lower limbs of the human body;

[0009] One end of the support module is pivotally connected to the balance module, and the rotation axis is at the same height as the human hip joint, and the support module is a retractable structure;

[0010] The control module is placed outside the wearable system, and is configured to receive electromyographic signals to automatically alarm when falling, send positioning, and control the support module to provide support.

[0011] Furthermore, the intelligent knee pad includes a sleeve-type soft knee pad and three wireless surface electromyography testing systems. Both ends of the sleeve-type soft knee pad are tightened and fixed to the human thigh and calf by Velcro. The three wireless surface electromyography testing systems are respectively located at the medial gastrocnemius muscle, tibialis anterior muscle, and rectus femoris muscle of the human lower limbs, and are configured to detect and process the electromyography signals at the moment of falling, and wirelessly transmit the electromyography signals to the control module.

[0012] Furthermore, the wearable system includes a rigid connector, a protective pad, and a strap. One end of the rigid connector is located at the lower side of the human hip joint, and the other end is located at the human waist, serving as a connection between the human body and the balance module and the strap. The protective pad is located on the inner side of the rigid connector.

[0013] Furthermore, the strap includes a first strap and a second strap, which are respectively located at the connection between the rigid connector and the human waist and at the connection with the lower side of the human hip joint, and are used to fix the human body and the rigid connector.

[0014] Furthermore, the balancing module includes a shell, a balancing frame, and a connecting shaft. The shell and the rigid connecting member are connected by bolts. Buffer foam is installed on the top of the shell. Limit blocks are provided on both sides of the shell. The two ends of the balancing frame are pivotally connected to the shell in the sagittal plane of the human body through the connecting shaft, and the height of the rotation axis is consistent with the height of the hip joint.

[0015] Further, the shell is provided with a first guide hole and a second guide hole, the balance frame is provided with a third guide hole, a fourth guide hole, a fifth guide hole, and a sixth guide hole, the connecting shaft includes a first connecting shaft, a second connecting shaft, and a third connecting shaft, one end of the first connecting shaft and the second connecting shaft respectively passes through the first guide hole and the second guide hole of the shell and are fixed by a nut, and the other end is respectively connected to the third guide hole and the fourth guide hole of the balance frame by bearings, both ends of the third connecting shaft pass through the fifth guide hole and the sixth guide hole of the balance frame and are fixed by nuts, and the middle section is connected to the support module by a bearing.

[0016] Furthermore, the support module includes an upper support rod, a lower support rod, and a compression spring, one end of the upper support rod is connected to the third connecting shaft, and the other end is located inside the lower support rod, the lower support rod is tubular and only opened at the upper end, and the bottom of the lower support rod is provided with a non-slip rubber head to achieve protection during support, the compression spring is located inside the lower support rod, one end contacts the bottom surface of the upper support rod, and the other end contacts the bottom surface inside the lower support rod to achieve assistance for the extension of the lower support rod, the upper support rod is provided with a seventh guide hole, and the third connecting shaft is connected to the seventh guide hole of the upper support rod through a bearing.

[0017] Furthermore, the support module also includes a limit key, one end of the limit key is placed in the key slot at the bottom end of the upper support rod, and a spring is installed between the bottom surface of the key slot, and the other end is placed in the guide slot of the lower support rod, so that the lower support rod can be extended along the length direction, and when the lower support rod is extended into place, the other end of the limit key can be accurately aligned with the limit hole at the top of the lower support rod to achieve automatic limiting when the lower support rod is extended.

[0018] Furthermore, the control module includes a functional module and a DC electromagnet push rod. The control module is located at the lower part of the shell and is connected to the rigid connector. The functional module is configured to receive the electromyographic signal transmitted by the wireless surface electromyography testing system to realize automatic alarm, positioning and control of the movement of the DC electromagnet push rod when a fall occurs. The DC electromagnet push rod is configured to limit the position when the support module contracts and to receive the signal from the functional module to automatically release the limit and release the lower support rod when a fall occurs, so as to achieve extension of the lower support rod.

[0019] Another object of the present invention is to provide a method for using a fall prevention device based on brain-machine fusion perception of human joint position and motion, comprising the following steps:

[0020] Step 1. First, wipe the knee joint of the thigh with medical alcohol, put the smart knee brace on the human knee joint, adjust the knee joint position of the smart knee brace to align it with the human knee joint position, and tighten the smart knee brace with Velcro. At this time, the electrodes placed in the smart knee brace will align with the medial gastrocnemius muscle, tibialis anterior muscle, and rectus femoris muscle of the lower limbs;

[0021] Step 2: Assemble the balance module, support module, control module, and wearable system;

[0022] Step 3: Fix the device assembled in step 2 to the corresponding part of the human body through the straps of the wearable system, and adjust it so that the axis of the connecting shaft of the balance module is aligned with the rotation axis of the human hip joint.

[0023] In combination with the above technical solutions and the technical problems solved, please analyze the advantages and positive effects of the technical solutions to be protected by the present invention from the following aspects:

[0024] First, in view of the technical problems existing in the above-mentioned prior art, some creative technical effects are brought about after solving the problems. The specific description is as follows:

[0025] (1) The system adopts the method of electromyographic signal detection and rigid structure support. By collecting the characteristic electromyographic signals before a fall occurs, the mechanical support device is automatically triggered to provide support to ensure safety. This realizes the whole process coverage from the detection and processing of electromyographic signals of specific muscle groups before a fall to the rigid support protection, alarm, and positioning of the human body during a fall.

[0026] (2) A balance ring is provided between the outer shell and the support rod, and the balance ring is connected to both the outer shell and the support rod, while the support rod is not connected to the outer shell. Thus, after the limit is released, the support rod can always remain in a vertical state under the action of gravity, automatically forming a certain angle with the tilted body, achieving rapid support and effectively ensuring the safety of the person. At the same time, the rotation center of the support rod is aligned with the rotation axis of the hip joint, ensuring the stability of the support without affecting the normal walking of the human body.

[0027] (3) A sleeve-type soft knee pad is used to wrap the wireless surface electromyography testing system at the knee joint to directly detect and process the electromyographic signals of the three specific muscle groups related to falls, namely the medial gastrocnemius, tibialis anterior, and rectus femoris, while also playing a certain protective role for the knee joint.

[0028] The present invention discloses a myoelectric fall prevention device based on brain-machine fusion perception artificial intelligence proprioception, including a brain-machine fusion perception interface, an intelligent kneepad, a wearable system, a balance module, a support module, and a control module. The external information input to the human body sensor is converted (encoded) into an electrical signal, and the signal is transmitted to the sensory nerve through an electrode implanted in the brain, thereby realizing the reconstruction of the sensory function. The intelligent kneepad is placed at the human knee joint, and the intelligent kneepad is configured to detect and process the characteristic muscle electromyographic signal when falling. The wearable system is connected to the waist, buttocks, and thigh of the human body. The balance module is placed outside the human hip joint. The balance module is connected to the wearable system. The balance module is configured to always keep the support module perpendicular to the ground and not interfere with the normal movement of the lower limbs of the human body. One end of the support module is pivotally connected to the balance module, and the rotation axis is at the same height as the human hip joint. The support module is a retractable structure. The control module is placed outside the wearable system. The control module is configured to receive the electromyographic signal to realize automatic alarm, send positioning, and control the support module to support when falling.

[0029] Second, the technical solution of the present invention solves the following major technical problems of human fall prevention devices in the prior art in industrial applications and has achieved significant technical progress:

[0030] 1. Delayed response and inaccurate detection of existing fall prevention devices

[0031] The existing fall prevention devices often rely on simple acceleration sensors or angle sensors to detect human falls. This method is easily interfered by the external environment or human activities, resulting in inaccurate detection and delayed response. Especially in the brief moment when a fall occurs, the device reaction time often cannot catch the signal before the fall in time, making it impossible to effectively prevent the fall.

[0032] Significant technical advancements of the present invention:

[0033] The present invention integrates brain-computer perception and surface electromyography testing technology to monitor the electromyographic signals near the human knee joint in real time, and can more accurately capture the characteristic muscle activity signals before a fall. This signal is closely related to the physiological response to a fall, and can predict the risk of a fall earlier and more accurately than traditional physical sensors, significantly improving the accuracy and reaction speed of detection. At the same time, the control module can quickly unlock the support module in a short time, immediately support the human body, and avoid falling.

[0034] 2. Existing preventive devices cannot effectively provide timely physical support

[0035] Most of the existing fall prevention devices are alarm systems that cannot provide physical support when a fall occurs, resulting in the inability to prevent the fall even though the risk of falling is detected. In addition, the existing support devices are often bulky in design, affecting the freedom of human movement, or only provide support after a fall occurs, which cannot achieve the effect of prevention.

[0036] Significant technical advancements of the present invention:

[0037] The present invention introduces a combination of intelligent knee pads and a wearable balance support system. When a danger signal is detected before a fall occurs, the support module can be quickly extended and fixed to the ground to provide effective support to prevent a fall. By aligning the balance module with the height of the human hip joint, the support module can achieve rapid support before a fall without interfering with normal activities, ensuring the stability of the human body. The device has good wearability, and the user can walk and move normally without feeling restrained by the support device.

[0038] 3. Existing devices are not suitable and comfortable enough

[0039] Traditional fall prevention devices are often complex in structure, cumbersome to operate, and poor in comfort, which affects the user's daily activities. At the same time, the detection modules and support modules of many devices are difficult to flexibly adjust and cannot adapt to the needs or physical characteristics of different users.

[0040] Significant technical advancements of the present invention:

[0041] The present invention significantly improves the comfort and applicability of the device through the design of smart kneepads, wearable systems and flexible support modules. The smart kneepad is light and comfortable, and is tightened and fixed with Velcro. The electrode position can adapt to the physical characteristics of different users to ensure that the device can fit the user closely. The support module is designed as a retractable structure, which can automatically unlock and support the human body when there is a risk of falling, and will not affect the user's activities under normal conditions. The straps and pads of the wearable system provide a comfortable wearing experience. The overall device is light and easy to wear, meeting the user's needs for long-term wear.

[0042] 4. The alarm and positioning functions of existing devices are not perfect

[0043] Although many existing fall detection devices have alarm functions, they often fail to send accurate location information to guardians or external emergency systems in a timely manner, resulting in delayed rescue response. In addition, some devices lack the function of locating after a fall, which affects emergency response after the accident.

[0044] Significant technical advancements of the present invention:

[0045] The control module of the present invention can not only automatically send an alarm when a fall occurs, but also integrates a positioning function, which can send user location information in real time to ensure that external guardians or emergency systems can respond quickly. This function significantly improves the rescue efficiency after a fall and ensures the safety of the user.

[0046] Through the above-mentioned technological innovations, the present invention has made significant progress in the field of fall prevention, improved the accuracy of detection and the speed of response, realized the function of real-time support to prevent falls, and has high comfort and user-friendliness, solving many problems in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a structural diagram of a fall prevention device based on brain-machine fusion perception of human joint position and motion provided by an embodiment of the present invention;

[0048] Figure 2 It is an overall schematic diagram of the mechanical part of a preferred embodiment provided by the embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram of a smart knee brace according to a preferred embodiment of the present invention;

[0050] Figure 4 Schematic diagram of a wireless surface electromyography testing system according to a preferred embodiment of the present invention;

[0051] Figure 5 is a schematic diagram of a wearable system according to a preferred embodiment of the present invention;

[0052] Figure 6 is a schematic diagram of a balancing module of a preferred embodiment provided by an embodiment of the present invention;

[0053] Figure 7 The embodiment of the present invention provides Figure 6 Schematic diagram of the shell;

[0054] Figure 8 The embodiment of the present invention provides Figure 6 Schematic diagram of the gimbal;

[0055] Fig. 9 The embodiment of the present invention provides Figure 6 Schematic diagram of the connecting shaft;

[0056] Fig.10 is a schematic diagram of a support module of a preferred embodiment provided by an embodiment of the present invention;

[0057] Fig.11 The embodiment of the present invention provides Fig.10 Schematic diagram of the upper support rod;

[0058] Fig.12 The embodiment of the present invention provides Fig.10 Schematic diagram of the lower support rod;

[0059] Fig.13 The embodiment of the present invention provides Fig.10 Schematic diagram of the limit key;

[0060] Fig.14 The embodiment of the present invention provides Fig.10 Schematic diagram of compression spring;

[0061] Fig.15 is a schematic diagram of a control module of a preferred embodiment provided by an embodiment of the present invention;

[0062] Fig.16 It is a flow chart of a method for using a fall prevention device based on brain-machine fusion perception of human joint position and motion provided by an embodiment of the present invention;

[0063] Fig.17 It is a comparison diagram of the use effects provided by the embodiments of the present invention;

[0064] Fig.18is a schematic diagram of the relationship between the acceleration SV, UFT, and LFT in a stable state provided by an embodiment of the present invention;

[0065] Fig.19 It is a schematic diagram of the relationship between the acceleration SV, UFT, and LFT in a falling state provided by an embodiment of the present invention.

[0066] In the figure: 1. Intelligent knee pad; 100. Sleeve-type soft knee pad; 101. Wireless surface electromyography test system; 2. Wearable system; 200. Rigid connector; 201. Pad; 202. Strap; 3. Balance module; 300. Shell; 3001. First guide hole; 3002. Second guide hole; 3003. Buffer foam; 301. Balance frame; 3011. Third guide hole; 3012. Fourth guide hole; 3013. Fifth guide hole; 3014. The sixth guide hole; 302, the connecting shaft; 3021, the first connecting shaft; 3022, the second connecting shaft; 3023, the third connecting shaft; 4, the supporting module; 400, the upper supporting rod; 4001, the seventh guide hole; 4002, the limit key slot; 401, the lower supporting rod; 4011, the eighth guide hole; 4012, the ninth guide hole; 402, the limit key; 403, the compression spring; 5, the control module; 500, the functional module; 501, the DC electromagnet push rod. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0068] like Figure 1-15 As shown, an embodiment of the present invention provides a fall prevention device based on brain-machine fusion perception of human joint position and motion, comprising:

[0069] Intelligent kneepad 1, wearable system 2, balance module 3, support module 4, control module 5, the intelligent kneepad 1 is placed at the human knee joint, the intelligent kneepad 1 is configured to detect and process characteristic muscle electromyographic signals during a fall, the wearable system 2 is connected to the human waist, buttocks, and thighs, the balance module 3 is placed on the outside of the human hip joint, the balance module 3 is connected to the wearable system 2, the balance module 3 is configured to always keep the support module 4 perpendicular to the ground and not interfere with the normal movement of the human lower limbs, one end of the support module 4 is pivotally connected to the balance module 3, and the rotation axis is at the same height as the human hip joint, the support module 4 is a retractable structure, the control module 5 is placed on the outside of the wearable system 2, and the control module 5 is configured to receive electromyographic signals to automatically alarm, send positioning, and control the support module 4 to provide support when falling.

[0070] The human joint position and motion sense fall prevention device provided by the present invention based on brain-machine fusion perception mainly realizes real-time fall prevention and protection through the coordinated work of intelligent knee pads, wearable systems, balance modules, support modules and control modules. The device timely identifies possible fall risks through real-time monitoring of human electromyographic signals and provides preventive support, thereby reducing the occurrence of fall accidents. The specific working principle is as follows:

[0071] First, the smart knee brace 1 detects electromyographic signals in real time through sensors placed at the human knee joint. These signals reflect the muscle activity status around the knee joint. By processing these signals, the system can identify abnormal muscle activity characteristics related to falls. When an abnormal signal is detected, the smart knee brace immediately transmits the signal to the control module to indicate a potential fall risk.

[0072] Then, the wearable system 2 monitors the posture and movement state of the human body in real time by connecting to the waist, hips, thighs and other parts of the human body, and collects the movement data of various parts of the human body through the integrated inertial measurement unit and sensors. These data can reflect the balance of the human body in different situations, provide real-time reference for the balance module, and thus achieve accurate balance perception and adjustment.

[0073] When the balance of the human body is unstable or the electromyographic signal is abnormal, the balance module 3 will automatically adjust the position and direction of the support module through the feedback of the wearable system. The balance module senses the posture of the human hip joint and always keeps the support module perpendicular to the ground to ensure that it provides effective support without interfering with normal lower limb movement. The rotation axis of the balance module is at the same height as the human hip joint, so as to ensure that the support point of the support module can be dynamically adjusted with the movement of the human body.

[0074] Finally, after receiving the fall signal, the control module 5 immediately performs a support action through the telescopic structure of the support module 4 to prevent the fall. The control module also has alarm and positioning functions. Once a fall occurs, the system will automatically alarm and send location information to ensure timely rescue. The support module quickly adjusts the length and support force through the instructions of the control module to form support for the human body and avoid further aggravation of the fall. The overall system uses brain-computer fusion technology to achieve timely prediction and intervention before a fall, providing users with active and intelligent protection.

[0075] The intelligent knee pad 1 provided in the embodiment of the present invention comprises a sleeve-type soft knee pad 100 and three wireless surface electromyography testing systems 101. Both ends of the sleeve-type soft knee pad 100 are tightened and fixed to the human thigh and calf by Velcro. The three wireless surface electromyography testing systems 101 are respectively located at the medial gastrocnemius muscle, tibialis anterior muscle, and rectus femoris muscle of the human lower limb, and are configured to detect and process the electromyography signal at the moment of falling, and wirelessly transmit the electromyography signal to the control module 5.

[0076] The wearable system 2 provided in an embodiment of the present invention includes a rigid connector 200, a protective pad 201, and a strap 202. One end of the rigid connector 200 is located at the lower side of the human hip joint, and the other end is located at the human waist, serving as a connection between the human body and the balance module 3 and the strap 202. The protective pad 201 is located on the inner side of the rigid connector 200.

[0077] The strap 202 provided in the embodiment of the present invention includes a first strap 202 and a second strap 202 , which are respectively located at the connection between the rigid connector 200 and the human waist and at the connection with the lower side of the human hip joint, and are used to fix the human body and the rigid connector 200 .

[0078] The balancing module 3 provided in the embodiment of the present invention includes a shell 300, a balancing frame 301, and a connecting shaft. The shell 300 is connected to the rigid connecting member 200 by bolts. A cushioning foam 3003 is installed on the top of the shell 300. Limit blocks are provided on both sides of the shell 300. The two ends of the balancing frame 301 are pivotally connected to the shell 300 in the sagittal plane of the human body through the connecting shaft, and the height of the rotation axis is consistent with the height of the hip joint.

[0079] The housing 300 provided in the embodiment of the present invention is provided with a first guide hole 3001 and a second guide hole 3002, the balancing frame 301 is provided with a third guide hole 3011, a fourth guide hole 3012, a fifth guide hole 3013, and a sixth guide hole 3014, the connecting shaft includes a first connecting shaft 3021, a second connecting shaft 3022, and a third connecting shaft 3023, one end of the first connecting shaft 3021 and the second connecting shaft 3022 respectively pass through the first guide hole 3001 and the second guide hole 3002 of the housing 300 and are fixed by nuts, and the other ends are respectively connected to the third guide hole 3011 and the fourth guide hole 3012 of the balancing frame 301 through bearings, both ends of the third connecting shaft 3023 pass through the fifth guide hole 3013 and the sixth guide hole 3014 of the balancing frame 301 and are fixed by nuts, and the middle section is connected to the support module 4 through a bearing.

[0080] The support module 4 provided by the embodiment of the present invention includes an upper support rod 400, a lower support rod 401, and a compression spring 403. One end of the upper support rod 400 is connected to the third connecting shaft 3023, and the other end is located inside the lower support rod 401. The lower support rod 401 is tubular and only opened at the upper end, and the bottom of the lower support rod 401 is provided with an anti-slip rubber head to achieve protection during support. The compression spring 403 is located inside the lower support rod 401, one end of which contacts the bottom surface of the upper support rod 400, and the other end contacts the bottom surface inside the lower support rod 401 to achieve assistance in extending the lower support rod 401. The upper support rod 400 is provided with a seventh guide hole 4001, and the third connecting shaft 3023 is connected to the seventh guide hole 4001 of the upper support rod 400 through a bearing.

[0081] The support module 4 provided in the embodiment of the present invention also includes a limit key 402, one end of the limit key 402 is placed in the bottom key slot of the upper support rod 400, and a spring is installed between the bottom surface of the key slot, and the other end is placed in the guide slot of the lower support rod 401, so that the lower support rod 401 can be extended along the length direction, and when the lower support rod 401 is extended into place, the other end of the limit key 402 can be accurately aligned with the limit hole at the top of the lower support rod 401 to achieve automatic limiting when the lower support rod 401 is extended.

[0082] The control module 5 provided in the embodiment of the present invention includes a functional module 500 and a DC electromagnet push rod 501. The control module 5 is located at the lower part of the shell 300 and is connected to the rigid connector 200. The functional module 500 is configured to receive the electromyographic signal transmitted by the wireless surface electromyography testing system 101, to realize automatic alarm, positioning, and control of the movement of the DC electromagnet push rod 501 when falling. The DC electromagnet push rod 501 is configured to limit when the support module 4 contracts and to receive the signal of the functional module 500 when falling to automatically release the limit and release the lower support rod 401, so as to realize the extension of the lower support rod 401.

[0083] The intelligent kneepad device of the present invention is based on brain-machine fusion technology. It monitors and processes the electromyographic signals of key muscles of the lower limbs of the human body in real time, automatically triggers the protection mechanism when a fall signal is detected, and effectively prevents human falls and reduces injuries. The intelligent kneepad 1 is the core detection unit of the device, which is equipped with three wireless surface electromyographic test systems, which are respectively located at the medial gastrocnemius muscle, tibialis anterior muscle and rectus femoris muscle of the human body. These sensors fix the soft kneepad to the human thigh and calf with Velcro, and can detect the electromyographic signals related to falls in real time. These signals are processed and wirelessly transmitted to the control module 5, realizing real-time monitoring of the muscle status, so that it can quickly determine whether the human body is in a state of risk of falling.

[0084] The wearable system 2 of the present invention tightly combines the knee pad, balance module and the human waist and thigh through the structure of the rigid connector 200 and the strap 202. One end of the rigid connector is located at the lower side of the hip joint, and the other end is located at the human waist, and comfortable protection is provided through the pad 201. The first and second straps are used to fix the wearable system to the waist and hip joint of the human body, respectively, to ensure stability in daily activities. The rigid connector not only provides stable support for the system, but also serves to connect the balance module and the support module, ensuring that the device can maintain a good balance at all times.

[0085] The key function of the balance module 3 is to ensure that the support module can pivot flexibly through the combination of the housing 300, the balance frame 301 and the connecting shaft. The housing of the balance module is fixed with a rigid connector by bolts and a cushioning foam is attached to the outside to provide additional shock protection in case of a fall. The balance frame is connected to the inside of the housing through the connecting shaft and can pivot in the sagittal plane to ensure that the rotation axis of the support module is aligned with the height of the human hip joint. This structural design allows the balance module to move freely when the human body is moving without interfering with normal walking and movement.

[0086] The support module 4 is a key component that provides physical support when falling. The module consists of an upper support rod 400, a lower support rod 401 and a compression spring 403. The support rod is connected to the balance frame through a third connecting axis and can be extended and retracted along the length of the body. The non-slip rubber head at the bottom of the lower support rod ensures stability during support, while the internal compression spring provides additional assistance to help the support rod extend quickly when receiving a control signal. The limit key 402 ensures that when the support rod is extended into place, it automatically locks the position to prevent the support rod from accidentally shrinking or not extending enough, ensuring stable and reliable support when falling.

[0087] The control module 5 determines whether the human body is in a falling state by receiving the electromyographic signal detected by the intelligent knee pad, and immediately triggers the protection mechanism. The functional module 500 transmits the processed electromyographic signal to the DC electromagnet push rod 501, and the movement of the push rod controls the limit state of the support module 4. Under normal circumstances, the DC electromagnet push rod keeps the support rod in a contracted state. Once a fall signal is detected, the push rod automatically releases the limit and releases the compression spring, so that the lower support rod quickly extends, thereby supporting the human body and preventing the occurrence of falls.

[0088] The workflow of the whole system includes the cooperation of multiple steps. First, the intelligent knee pad monitors the movement state of the lower limbs of the human body in real time through electromyographic signals, and transmits the signal to the control module after detecting abnormal muscle activity. Subsequently, the wearable system controls the position of the support rod through the balance module to ensure that the support module can quickly extend and contact the ground when falling, providing effective support. At the same time, the control module 5 also has alarm and positioning functions. When a fall is detected, it automatically issues an alarm and sends positioning information to external devices to ensure timely rescue.

[0089] like Fig.16 As shown, a method for using a fall prevention device based on brain-machine fusion perception of human joint position and motion provided by an embodiment of the present invention includes the following steps:

[0090] S101. First, wipe the knee joint of the thigh with medical alcohol, put the smart knee brace on the human knee joint, adjust the knee joint position of the smart knee brace to align with the human knee joint position, and tighten the smart knee brace with Velcro. At this time, the electrodes placed in the smart knee brace will be aligned with the medial gastrocnemius muscle, tibialis anterior muscle, and rectus femoris muscle of the lower limb;

[0091] S102, assembling a balance module, a support module, a control module, and a wearable system;

[0092] S103, fix the device assembled in S102 to the corresponding part of the human body through the straps of the wearable system, and adjust it so that the axis of the connecting shaft of the balance module is aligned with the rotation axis of the human hip joint.

[0093] The device of the present invention realizes the perception of human joint position and movement through brain-machine fusion technology, and provides real-time fall prevention function. The working principle of the method of use can be divided into multiple steps, which gradually realize the installation of the device, signal monitoring and triggering of the automatic support mechanism.

[0094] First, in step S101, wipe the knee joint with medical alcohol to ensure that the skin surface is clean and free of sweat or grease, which is conducive to close contact of the electrodes and stable transmission of signals. The smart knee pad is put on the knee joint, and the wireless surface electromyography test system inside the knee pad is configured to accurately align the three key muscle points of the medial gastrocnemius, tibialis anterior and rectus femoris of the lower limbs. The device is fixed with Velcro to ensure that it does not shift in position during exercise. At this time, the electrodes begin to monitor the electromyographic signals of the muscles near the human knee joint in real time to capture the characteristic muscle activity before the fall occurs.

[0095] In step S102, the balance module, support module, control module and wearable system are assembled. The balance module is connected to the waist and hip joints of the human body through rigid connectors, and the support module is installed on the rotating axis of the balance module and can rotate freely when the hip joint moves. The support module is a retractable structure designed to extend and support the human body when falling, while the control module is responsible for receiving electromyographic signals in real time and making judgments and controls. When there is a risk of falling, the control module will activate the support module through a signal transmission mechanism.

[0096] Next, in step S103, the device is fixed to the corresponding position of the human body through the straps of the wearable system. The straps fit tightly to the waist, thigh, and hip joint areas of the human body, and the stability of the device during movement is ensured by the pads and rigid connectors. During the installation process, the connection axis of the balance module is aligned with the rotation axis of the human hip joint, which prevents the device from interfering with the natural movement of the human body during normal movement, and ensures that the support module can accurately position the support function at the moment of falling.

[0097] The core of the working principle of the whole device is to determine whether there is a risk of falling by real-time monitoring of the electrical signals of the lower limb muscles. When the electromyographic signal shows characteristic changes before a fall, the wireless surface electromyographic test system in the smart kneepad transmits the signal wirelessly to the control module. The control module determines that a fall is about to occur by analyzing the signal, and immediately issues a command to control the release mechanism of the support module. At this time, the DC electromagnet push rod is activated, unlocking the limit device of the support rod, and the compression spring pops out quickly, causing the support rod to extend to the ground along the lower limbs of the human body.

[0098] The rapid extension of the support module ensures that the human body obtains sufficient support force before falling, and the anti-slip rubber head at the bottom of the support rod provides additional stability to prevent support failure or slipping. The entire action is completed almost at the moment of falling. Through the system's rapid response mechanism, it can effectively avoid falling or reduce the damage caused by falling. At the same time, the control module will automatically trigger the alarm and positioning function to ensure that the external guardian can be informed of the fall information in time and locate the fall position, providing convenience for emergency rescue after the fall.

[0099] The working principle of the intelligent control method provided by the embodiment of the present invention is to achieve fall prevention and real-time response through an intelligent brain-machine fusion perception system and multi-module collaboration. The following is a detailed working process of the system divided into six stages for explanation:

[0100] 1. EMG signal collection and preliminary analysis: The wireless surface electromyography test system in the smart knee brace collects lower limb electromyography signals in real time through electrodes attached to the gastrocnemius, tibialis anterior and rectus femoris muscles of the lower limbs. When the human body walks, stands, squats, and other movements, the microcurrent signals generated by the muscles will be captured by the sensor. The smart knee brace sends these signals to the control module through the wireless transmission module. The control module performs preliminary processing according to the preset algorithm, and combines the human body movement information collected by the sensor to determine whether there are any abnormalities, such as signs of unstable gait or loss of balance.

[0101] 2. Fall risk judgment and deep learning analysis: After receiving the signal from the smart knee pad, the control module will conduct a comprehensive analysis of the electromyographic signal and the sensor data from the balance module. In order to improve the accuracy of identifying the precursors of falls, the control module has a built-in self-learning algorithm, which will be continuously updated and optimized. Based on multiple historical electromyographic signal samples and fall data, the deep learning model training is used to predict the characteristics of falls. When the system finds that certain characteristic signals match the key characteristics before a fall, the system will further determine whether there is a high risk of falling.

[0102] 3. Real-time fall detection and alarm: Once the control module confirms that there is a risk of falling, the system immediately sends an alarm message to the preset equipment or personnel (such as mobile devices or emergency services) through the wireless communication network to inform the current user that a fall may be imminent. At the same time, the positioning module is activated to transmit the user's real-time location to relevant equipment for emergency treatment. This alarm function ensures that the fall prevention system can still provide safety even if no one else is present.

[0103] 4. Automatic deployment and support process of the support module: When a fall signal is detected, the control module quickly instructs the support module to move. The support module is aligned with the human body's hip joint height through the balance module and deployed with its rotation pivot as the center. The compression spring in the support rod is released under the action of the electromagnet push rod, pushing the lower support rod to extend and contact the ground. The automatic deployment of the support module is controlled by the limit sensor to ensure that the support rod can be appropriately extended according to the actual needs of the human body, thereby stabilizing the human body posture and avoiding the occurrence of falls.

[0104] 5. Dynamic adjustment during support: After the support module is unfolded, the system will continuously monitor the support status and adjust the support angle and length in real time according to the posture and balance of the human body. Through the feedback of the balance module, the support module can adapt to the changes in the posture of the human body and dynamically adjust the direction of the support point to ensure that the user can get stable support in different situations and avoid the risk of secondary falls caused by improper posture. At the same time, the anti-slip device at the bottom of the support module can enhance the ground friction of the support rod to ensure a more reliable support effect.

[0105] 6. Support module reset and system recovery: When the control module detects that the human body has regained balance, or confirms that the user is standing safely through the monitored electromyographic signal, the system will control the support module to automatically reset. The DC electromagnet push rod works again, retracts the support rod to the initial state and limits it. After the support module is reset, the system returns to the monitoring state and is ready to prevent and deal with falls again at any time. The entire process realizes full-process automated control from detection to response and then to reset, ensuring the daily safety of users.

[0106] Through the above six steps, the device of the present invention can effectively prevent falls, provide efficient emergency support and alarm mechanism, and ensure the intelligent operation of the system.

[0107] The relevant experimental data of the technical effects obtained by the embodiments of the present invention are as follows.

[0108] The comparative effects between the intervention group and the control group are shown in Table 1, Table 2, Fig.17 , Fig.18 and Fig.19 shown.

[0109] Table 1

[0110]

[0111] Notes: * p<0.05; a Wilcoxon signed-rank test.

[0112] Table 2

[0113]

[0114] Notes: * p<0.05; ** p<0.001; Lawton IADL, Lawton Instrumental Activities of Daily Living Assessment Scale; a Paired samples t-test.

[0115] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A fall prevention device based on brain-machine fusion perception of human joint position and motion, characterized in that: Including smart knee pads, wearable system, balance module, support module, control module; The smart kneepad is placed at the knee joint of a human body, and is configured to detect and process characteristic muscle electromyographic signals during a fall. The wearable system is connected to the waist, buttocks, and thighs of the human body, and the balance module is placed outside the hip joint of the human body; The balancing module is connected to the wearable system, and the balancing module is configured to always keep the supporting module perpendicular to the ground and not interfere with the normal movement of the lower limbs of the human body; One end of the support module is pivotally connected to the balance module, and the rotation axis is at the same height as the human hip joint, and the support module is a retractable structure; The control module is placed outside the wearable system, and is configured to receive electromyographic signals to automatically alarm when falling, send positioning, and control the support module to provide support.

2. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1 is characterized in that: The intelligent knee pad includes a sleeve-type soft knee pad and three wireless surface electromyography testing systems. Both ends of the sleeve-type soft knee pad are tightened and fixed to the human thigh and calf by Velcro. The three wireless surface electromyography testing systems are respectively located at the medial gastrocnemius muscle, tibialis anterior muscle, and rectus femoris muscle of the human lower limbs, and are configured to detect and process the electromyography signals at the moment of falling, and wirelessly transmit the electromyography signals to the control module.

3. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1, characterized in that: The wearable system includes a rigid connector, a protective pad, and a strap. One end of the rigid connector is located at the lower side of the human hip joint, and the other end is located at the human waist, serving as a connection between the human body and the balance module and the strap. The protective pad is located on the inner side of the rigid connector.

4. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 3 is characterized in that: The binding strap comprises a first binding strap and a second binding strap, which are respectively located at the connection between the rigid connector and the waist of the human body and at the connection between the rigid connector and the lower side of the hip joint of the human body, and are used to fix the human body and the rigid connector.

5. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1, characterized in that: The balancing module includes a shell, a balancing frame, and a connecting shaft. The shell is connected to the rigid connecting member by bolts. Buffer foam is installed on the top of the shell. Limit blocks are provided on both sides of the shell. The two ends of the balancing frame are pivotally connected to the shell in the sagittal plane of the human body through the connecting shaft, and the height of the rotation axis is consistent with the height of the hip joint.

6. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 5, characterized in that: The shell is provided with a first guide hole and a second guide hole, the balance frame is provided with a third guide hole, a fourth guide hole, a fifth guide hole and a sixth guide hole, the connecting shaft includes a first connecting shaft, a second connecting shaft and a third connecting shaft, one end of the first connecting shaft and the second connecting shaft respectively passes through the first guide hole and the second guide hole of the shell and are fixed by a nut, and the other end is respectively connected to the third guide hole and the fourth guide hole of the balance frame by bearings, both ends of the third connecting shaft pass through the fifth guide hole and the sixth guide hole of the balance frame and are fixed by nuts, and the middle section is connected to the support module by a bearing.

7. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1, characterized in that: The support module includes an upper support rod, a lower support rod, and a compression spring, one end of the upper support rod is connected to the third connecting shaft, and the other end is located inside the lower support rod, the lower support rod is tubular and only opened at the upper end, and the bottom of the lower support rod is provided with a non-slip rubber head to achieve protection during support, the compression spring is located inside the lower support rod, one end contacts the bottom surface of the upper support rod, and the other end contacts the bottom surface of the lower support rod to achieve assistance for the extension of the lower support rod, the upper support rod is provided with a seventh guide hole, and the third connecting shaft is connected to the seventh guide hole of the upper support rod through a bearing.

8. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1, characterized in that: The support module also includes a limit key, one end of the limit key is placed in the key slot at the bottom end of the upper support rod, and a spring is installed between the limit key and the bottom surface of the key slot, and the other end is placed in the guide slot of the lower support rod, so that the lower support rod can be extended along the length direction, and when the lower support rod is extended into place, the other end of the limit key can be accurately aligned with the limit hole at the top of the lower support rod to achieve automatic limiting when the lower support rod is extended.

9. The fall prevention device based on brain-machine fusion perception of human joint position and motion as claimed in claim 1, characterized in that: The control module includes a functional module and a DC electromagnet push rod. The control module is located at the lower part of the shell and is connected to the rigid connector. The functional module is configured to receive the electromyographic signal transmitted by the wireless surface electromyography testing system to realize automatic alarm, positioning and control of the movement of the DC electromagnet push rod when a fall occurs. The DC electromagnet push rod is configured to limit the position when the support module contracts and to receive the signal from the functional module to automatically release the limit and release the lower support rod when a fall occurs, so as to achieve extension of the lower support rod.

10. A control method for an intelligent fall prevention device based on brain-machine fusion perception of human joint position and motion, characterized in that: The method comprises the following steps: a) Using the intelligent knee pad to collect and process the electromyographic signals of the human lower limbs in real time, and sending the data to the control module through the wireless transmission module; b) the control module analyzes the received electromyographic signal and sensor module data to determine whether there is a risk of falling; c) When a fall signal is detected, the control module automatically activates the support module for support and sends an alarm message and positioning data to the preset device.

11. The control method of the intelligent fall prevention device according to claim 1, characterized in that: The control method further comprises the following steps: a) The control module continuously monitors the balance state and electromyographic signals of the human body based on a self-learning algorithm, and optimizes the fall determination model by analyzing the characteristic signals before the fall multiple times; b) Using deep learning models, by learning from historical data, the precursors of falls can be predicted and the support module can be activated before a fall occurs.

12. The control method of the intelligent fall prevention device according to claim 1, characterized in that: The method further comprises the following steps: a) The control module monitors the state of the support module and adjusts the extension and retraction state of the support module according to the real-time environment and human body movements; b) In the non-falling state, the support module automatically remains in the retracted state. When a fall or high-risk action is detected, the control module sends a signal to trigger the support module to unfold, and adjusts the support amplitude and angle in real time through the limit sensor.

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