Intelligent anti-falling belt

Abstract

The invention relates to the technical field of medical instruments, and discloses an intelligent anti-falling belt which comprises a bionic muscle module, a monitoring module, a data processing module, a control module and a power supply module. The bionic muscle module is in a waistband shape and comprises a 3D knitted gradient fabric layer, a shear thickening fluid micro-capsule array layer and a shape memory alloy supporting net layer which are sequentially arranged from inside to outside. Through mutual cooperation of all the modules, real-time monitoring of the body posture of a wearer and the surrounding environment is achieved, the body posture of the wearer is adjusted in real time, active and passive supporting protection is provided, falling is prevented, the safety of the old is effectively protected, and the living quality and independence of the old are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to an intelligent anti-fall belt. Background Art

[0002] With the accelerating aging of society and the increasing number of elderly people, falls are a particularly prominent problem. Many elderly people suffer from underlying medical conditions and limited mobility, making falls a common occurrence. This can lead to hip fractures, paralysis, lifelong disability, and even death in severe cases. Furthermore, unattended elderly people lack timely medical attention after falls, delaying their condition. Current protective gear for the elderly, including elbow pads, vests, and belts, can help prevent injuries from falls.

[0003] Traditional fall protection gear mostly provides cushioning during a fall, but fails to effectively prevent or intervene before a fall occurs. For example, some inflatable protective gear needs to be inflated at the moment of a fall, but its response speed and reliability are limited, and it cannot proactively adjust the elderly person's body posture to prevent a fall. Summary of the Invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the present invention aims to provide an intelligent anti-fall belt.

[0005] The intelligent anti-fall belt of the present invention comprises:

[0006] The bionic muscle module is in the shape of a belt and includes a 3D knitted gradient fabric layer, a shear thickening fluid microcapsule array layer, and a shape memory alloy support mesh layer arranged in sequence from the inside to the outside;

[0007] A monitoring module, which is used to monitor the wearer's body posture information and surrounding environment information;

[0008] a data processing module, wherein the data processing module processes the body posture information and surrounding environment information to generate a three-dimensional motion posture model;

[0009] a control module, wherein the control module controls the local viscosity change of the shear thickening fluid in the microcapsule and the local deformation of the shape memory alloy according to the three-dimensional motion posture model to change the posture of the wearer and restore the wearer's balance;

[0010] A power supply module is used to supply power to the bionic muscle module, the monitoring module, the data processing module and the control module.

[0011] Preferably, the 3D knitted gradient fabric layer includes a middle waist area, two side waist areas and an edge area. The middle waist area is knitted with yarn having a linear density greater than 22.2tex, the two side waist areas are knitted with yarn having a linear density between 8.3-22.2tex, and the edge area is knitted with yarn having a linear density less than 8.3tex.

[0012] Preferably, the microcapsules are arranged in a hexagonal honeycomb structure and interconnected by microchannels.

[0013] Preferably, the shape memory alloy support mesh layer is embedded with glass fiber reinforced polyurethane material to form an arc-shaped support bar with a bionic curvature of the spine.

[0014] Preferably, the monitoring module includes a six-axis inertial sensor, a piezoelectric fiber array, a laser radar micromodule and an impedance sensor;

[0015] The six-axis inertial sensor is provided on the bionic muscle module and is used to collect the three-dimensional acceleration and three-dimensional angular velocity of the wearer's body;

[0016] The piezoelectric fiber array is embedded in the 3D knitted gradient fabric layer to detect local pressure distribution and identify the direction of the wearer's center of gravity deviation;

[0017] The laser radar micro-modules are distributed around the bionic muscle module to scan the height of ground obstacles, predict terrain risks, and promptly detect potential danger signals in the wearer's surrounding environment;

[0018] The impedance sensor is arranged outside the shear thickening fluid microcapsule, and the impedance sensor detects the deformation resistance of the bionic muscle module in real time;

[0019] The data processing module determines whether the wearer is at risk of falling based on the three-dimensional acceleration and three-dimensional angular velocity, the center of gravity offset direction, the potential danger signal and the deformation resistance;

[0020] If so, the control module dynamically adjusts the driving current to control the shear thickening fluid to change viscosity and the shape memory alloy to contract, ensuring that the bionic muscle module provides appropriate supporting force.

[0021] Preferably, the monitoring module also includes a temperature compensation module, which is in close contact with the shear thickening fluid microcapsule array and the shape memory alloy, and is used to monitor the ambient temperature and the operating temperature of the bionic muscle module in real time, and feed back the temperature data to the data processing module. The data processing module adjusts the driving current according to the temperature data to ensure the stability of the viscosity of the shear thickening fluid.

[0022] Preferably, it also includes a positioning module and a communication module. The positioning module and the communication module are integrated into the bionic muscle module. The positioning module obtains the wearer's location information in real time, and the communication module is used to send the location information to the guardian's mobile terminal in a timely manner.

[0023] Preferably, an alarm module is further included. When the wearer falls, the alarm module triggers an alarm and sends an emergency distress signal to the guardian through the communication module.

[0024] Preferably, it further includes a touch screen, which is arranged on the outside of the bionic muscle module, and the power supply module is integrated into the touch screen.

[0025] Preferably, the shear thickening fluid comprises, by mass percentage, 38%-45% of silicon dioxide nanoparticles, 50%-60% of polyethylene glycol base fluid, 1%-3% of boron carbide nanosheets, and 0.5%-1% of a boron-ester bond compound.

[0026] The advantage of the intelligent anti-fall belt described in the present invention is that, through the mutual cooperation between various modules, it can achieve real-time monitoring of the wearer's body posture and surrounding environment, adjust the wearer's body posture in real time, provide active and passive support and protection, prevent falls, effectively protect the safety of the elderly, and improve the quality of life and independence of the elderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic structural diagram of the intelligent anti-fall belt of the present invention;

[0028] Figure 2 Schematic diagram of the layered structure of the intelligent anti-fall belt of the present invention;

[0029] Figure 3 This is a module distribution diagram of the intelligent anti-fall belt of the present invention;

[0030] Figure 4 This is a force analysis diagram of the intelligent anti-fall belt of the present invention.

[0031] Description of reference numerals:

[0032] 1. 3D knitted gradient fabric layer, 2. shear thickening fluid microcapsule array layer, 3. shape memory alloy support mesh layer, 4. touch screen. DETAILED DESCRIPTION

[0033] In this embodiment, the wearer is described by taking an elderly person as an example.

[0034] like Figure 1-Figure 3As shown, the intelligent anti-fall belt disclosed in this embodiment includes a bionic muscle module, a monitoring module, a data processing module, a control module, a positioning module, a communication module, an alarm module and a touch screen 4.

[0035] Among them, the bionic muscle module is in the shape of a belt and serves as an execution module for adjusting the wearer's center of gravity in this embodiment. It includes a 3D knitted gradient fabric layer 1, a shear thickening fluid microcapsule array layer 2 and a shape memory alloy support mesh layer 3 arranged in sequence from the inside to the outside.

[0036] The 3D knitted gradient fabric layer 1 conforms to the skin around the waist, providing basic comfort and light compression support. Using three-dimensional weaving technology, the fabric has fiber distribution in the warp, weft, and vertical directions. Compared with traditional two-dimensional woven fabrics, 3D knitted fabrics have greater three-dimensionality and structure. This weaving method allows the fabric to better conform to the body's curves, providing even support and pressure distribution.

[0037] The 3D knitted gradient fabric layer 1 specifically includes a middle waist area, areas on both sides of the waist, and an edge area. The middle waist area is knitted with yarn having a linear density greater than 22.2tex, the areas on both sides of the waist are knitted with yarn having a linear density between 8.3-22.2tex, and the edge area is knitted with yarn having a linear density less than 8.3tex.

[0038] The middle area roughly corresponds to the lumbar spine area, including the narrow area around the navel and on both sides of the lumbar spine. This area is the core part of the human torso. The high line density provides strong support for the core part, stabilizes the waist, prevents excessive bending and twisting, reduces lumbar pressure, helps maintain correct posture, and provides sufficient support to prevent falls when the elderly have abnormal body posture.

[0039] The two side areas are located on both sides of the waist, extending from the core area to the sides, roughly corresponding to the side abdomen of the waist, and located between the lower edge of the ribs and the upper edge of the pelvis. This area is mainly involved in the lateral movement and posture adjustment of the body, such as side bending, twisting and other movements. The medium linear density yarn can assist the core area to maintain body balance, and can provide lateral support in time when the center of gravity of the elderly shifts, helping to adjust the body posture, while allowing a certain degree of natural movement. When the elderly body tilts to one side, the fabric in the middle area can generate corresponding reaction force to help correct the posture.

[0040] The low-density yarns in the edge area provide gentle compression, ensuring comfort without causing excessive restraint for the elderly. At the same time, it can still provide a certain degree of protection for the waist edge to prevent discomfort or injury caused by excessive local pressure.

[0041] The shear thickening fluid microcapsule array layer 2 is a microcapsule structure filled with shear thickening fluid (STF). When the shear thickening fluid is subjected to pressure or shear force, the viscosity will change significantly. In this embodiment, when the monitoring module detects that the elderly person's center of gravity is shifted, the shear thickening fluid can change from a fluid state to a semi-solid state in a short time (millisecond response), increase the local hardness, and thus form a rigid support structure. Figure 4 As shown in the figure, when the elderly lean forward, there is an angle between the upper and lower body, and the viscosity of the shear thickening fluid in the waist front module increases, causing expansion. The specific expansion direction is up and down. The up and down expanding STF can help the body restore balance by providing backward support force, reduce the possibility of falling, and prevent the center of gravity from moving forward too much, thereby enhancing the stability of the body. Specifically, since the elderly have a tendency to fall forward, the elderly's posture is different from Figure 4 Similarly, when the front waist belt expands, it will generate a diagonal upward and downward squeezing force, thereby helping the elderly to regain their balance. Of course, the upward and downward expansion is the best expansion direction, and other combinations of directions can also achieve similar effects, but the effects are different.

[0042] The microcapsules in this embodiment are arranged in a hexagonal honeycomb structure and interconnected by microchannels, allowing the shear-thickening fluid to be evenly distributed throughout the bionic muscle module. When the shear-thickening fluid in a certain area is subjected to pressure and undergoes a change in viscosity, the microchannels can quickly transmit this change to the surrounding fluid microcapsules, forming an overall support effect. This microchannel structure facilitates the rapid transmission of pressure signals, allowing the shear-thickening fluid to form effective support throughout the entire module in a short period of time, preventing the elderly person's center of gravity from deviating further.

[0043] In this embodiment, the shear thickening fluid comprises, by mass percentage, 38%-45% silica nanoparticles, 50-60% polyethylene glycol base liquid, 1-3% boron carbide nanosheets, and 0.5-1% boron ester bond compound. Specifically, the nano-silica has a particle size of 50-300 nanometers and a purity of >99.9%. As the main active ingredient in shear thickening, it achieves viscosity mutations through friction and collision between particles. The molecular weight of the glycol is 400-600 nanometers, which improves fluidity and reduces zero-shear viscosity (<1 Pa·s) while ensuring a thickening effect at high shear rates (viscosity can be increased by 1000 times). The boron carbide nanosheets have a thickness of <10 nanometers and a diameter of 200-500 nanometers, which improve thermal conductivity (>30 W / m·K) and prevent performance degradation caused by particle agglomeration. Boron-ester compounds can achieve self-repair of damaged microcapsules. Specifically, the boron atoms in boron-ester compounds (such as borate crosslinkers) have empty orbitals, which can form dynamic covalent bonds with hydroxyl (-OH) groups in the polyethylene glycol base liquid. This borate ester bond remains stable at room temperature, but when the microcapsule ruptures, causing localized stress concentration, the bond energy decreases to a reversible range. When the shear thickening fluid microcapsules are ruptured by external force, the borate bonds on the fracture surface are exposed to the polyethylene glycol environment, and the unreacted hydroxyl groups are re-coordinated with the boron atoms. The repair efficiency is >90% within 24 hours. The environmental moisture (H2O) acts as a catalyst to promote the hydrolysis-reesterification cycle of the borate bonds, achieving multiple self-repairs. The surface hydroxylated nano-SiO2 particles act as physical cross-linking points, which are combined with the polyethylene glycol segments through hydrogen bonds to limit the excessive movement of the borate bonds. At the same time, they provide high specific surface area active sites for the repair reaction, thereby increasing the recovery speed. The tensile strength recovery rate is increased from 78% to 92%. Boron carbide nanosheets enable the material to maintain stable repair performance in the range of -20°C to 80°C, and the temperature difference adaptability is increased by 40%, preventing the thermal decomposition of dynamic bonds during the self-repair process. Compared with the disposable airbag anti-fall in the prior art, the microcapsules of this embodiment can self-repair, can be used multiple times, and are more practical.

[0044] The shear thickening fluid microcapsules of this embodiment can be prepared according to the following method:

[0045] Step 1: Nanoparticle surface modification

[0046] The silica nanoparticles were immersed in 3-aminopropyltriethoxysilane (APTES) ethanol solution (concentration 2 wt%) and ultrasonically treated for 30 min (power 300 W) to form an amino surface to enhance the compatibility with PEG.

[0047] Step 2: Premixing the base fluid

[0048] The PEG base liquid was heated to 50° C., and the boron carbide nanosheets and dynamic crosslinker (compound containing boron ester bond) were added and magnetically stirred for 2 h (rotation speed 800 rpm) until uniform dispersion.

[0049] Step 3: High Shear Dispersion

[0050] The modified silica particles were added to the base liquid (polyethylene glycol) three times, with an interval of 10 minutes each time, and treated with a high-speed homogenizer (15000 rpm) for 1 hour to form a stable suspension.

[0051] Step 4: Microencapsulation

[0052] A W / O / W double emulsion was generated using a microfluidic chip (channel diameter 200 μm). The external phase was a polyurethane prepolymer solution (concentration 15 wt%). After curing, elastic microcapsules with a wall thickness of 50 μm were formed. The microcapsule diameter was controlled at 0.5-2 mm, and the internal STF filling rate was >95%.

[0053] Shape memory alloy (SMA) is a material that can change shape when subjected to thermal stimulation. In this embodiment, nickel-titanium alloy wire is generally used. Its basic principle is based on the shape memory effect, that is, when the SMA is heated to a certain temperature (transition temperature) or above, its internal crystal structure undergoes a transformation from martensite to austenite, thereby triggering its contraction behavior. When the data processing module determines that the elderly person is at risk of falling, it will immediately output a microcurrent to the SMA through the drive circuit. When the current passes through the nickel-titanium alloy wire, Joule heating is generated. Due to the Joule heating effect, the heat is quickly transferred to the alloy wire, causing its temperature to increase. The resistance value of nickel-titanium alloy wire is relatively high, and it can convert electrical energy into thermal energy in a short time, achieving rapid heating. As the temperature rises, the crystal structure inside the nickel-titanium alloy wire begins to transform. This phase change process is rapid, and the alloy wire can shrink by 15% in length within 0.2 seconds. This rapid contraction behavior can drive the 3D knitted gradient fabric to generate lateral tension, helping to adjust the elderly person's waist posture, thereby changing the elderly person's center of gravity.

[0054] The shape memory alloy support mesh layer 3 is embedded with glass fiber reinforced polyurethane material and forms an arc-shaped support strip with a bionic spinal curvature. The arc-shaped support strip with a bionic spinal curvature is designed based on the physiological curvature of the human spine. This arc-shaped design allows the support strip to naturally fit the elderly's waist curve. When the elderly's body twists, the arc-shaped support strip can better adapt to the movement trajectory of the waist and provide support that conforms to the natural physiological structure of the human body. The glass fiber reinforced polyurethane material has both high rigidity and a certain degree of toughness. The high strength and high modulus properties of the glass fiber provide the support strip with sufficient rigidity, enabling it to resist deformation when subjected to torsional forces, while the toughness of the polyurethane matrix ensures that the support strip will not suffer brittle fracture when subjected to large external forces. This combination of rigidity and flexibility allows the support strip to effectively provide support while adapting to a certain degree of deformation during the elderly's body twisting, avoiding excessive pressure or damage to the elderly's waist. When the elderly person's body twists, the arc-shaped support bar is subjected to a torsional force from the waist. Due to its rigidity, the support bar will generate a reaction torque in the opposite direction of the torsional force. This reaction torque is generated by the structural strength of the support bar itself and the contact with the waist. At the same time, the support bar works in conjunction with other modules such as shape memory alloys and shear thickening fluids. For example, when the shape memory alloy contracts and drives the 3D knitted gradient fabric to generate lateral tension, the arc-shaped support bar can effectively transfer this tension to other parts around the waist, enhancing the support effect. The rigid support structure formed by the hardening of the shear thickening fluid can also cooperate with the arc-shaped support bar to jointly resist the torque generated by the torsion of the body, further enhancing the support effect. In addition, during the resetting process of the shape memory alloy, the rigid structure of the arc-shaped support bar can help it return to its original shape, ensuring that the support performance of the belt is not affected.

[0055] The monitoring module is used to monitor the wearer's body posture information and surrounding environment information. Specifically, the monitoring module includes a six-axis inertial sensor, a piezoelectric fiber array, a laser radar micromodule, an impedance sensor, and a temperature compensation module.

[0056] The six-axis inertial sensor, installed on the bionic muscle module, collects three-dimensional acceleration (±16g) and angular velocity (±2000° / s) data at a frequency of 1kHz. This data can reflect changes in the elderly's body tilt angle and movement trajectory. For example, when the elderly lean forward or sideways, the acceleration and angular velocity data will change accordingly.

[0057] The piezoelectric fiber array is embedded in the 3D knitted gradient fabric layer 1 to detect the local pressure distribution (accuracy 0.1kPa) and identify the direction of center of gravity shift. If the elderly person's center of gravity shifts to one side, the pressure on the corresponding part will increase.

[0058] Micro-LiDAR modules are distributed around the bionic muscle module. Based on the time-of-flight (TOF) principle, they scan the height of obstacles on the ground (with an accuracy of ±5cm), predict terrain risks such as steps and slopes, and promptly detect potential danger signals in the wearer's surroundings. When an elderly person approaches terrain with a risk of falling, they can identify and issue a warning signal in advance, reminding them to pay attention.

[0059] Impedance sensors are positioned outside the shear-thickening fluid microcapsules to monitor the deformation resistance of the bionic muscle module in real time. Based on the mechanical properties of the elderly person's waist, the belt is divided into multiple zones, each with at least one impedance sensor installed. For example, the belt can be divided into five zones: front, back, left, right, and center, with one or more impedance sensors installed in each zone to achieve comprehensive monitoring of the entire waist. The density of impedance sensors is increased at key stress points and locations prone to deformation. For example, more sensors are placed at key locations such as the sacrum and bilateral kidneys to more accurately monitor mechanical changes in these areas. When the impedance sensors detect changes in resistance, the data processing module dynamically adjusts the microcurrent output to the shape memory alloy according to pre-set control strategies and algorithms. For example, if resistance increases, the processor increases the microcurrent to enhance the contractile force of the SMA; if resistance decreases, the microcurrent is appropriately reduced to maintain the proper contraction state.

[0060] The temperature compensation module, located in close proximity to the shear-thickening fluid microcapsule array and shape memory alloy, monitors the ambient temperature and the bionic muscle module's operating temperature in real time. This temperature data is fed back to the data processing module, which adjusts the drive current based on this temperature data to ensure stable shear-thickening fluid viscosity. In this embodiment, the temperature compensation module uses a PTC thermistor to maintain the module's operating temperature between 15°C and 40°C, ensuring stable shear-thickening fluid viscosity and ensuring control accuracy.

[0061] The data processing module processes body posture information and surrounding environment information to generate a three-dimensional motion posture model. Specifically, the data processing module determines whether the wearer is at risk of falling based on three-dimensional acceleration and angular velocity, center of gravity offset direction, potential danger signals, and deformation resistance. If so, the control module dynamically adjusts the drive current, controls the viscosity of the shear-thickening fluid, and contracts the shape memory alloy to ensure that the bionic muscle module provides appropriate support.

[0062] In this embodiment, the data processing module is a microprocessor (STM32H7), and the data transmission between each module is transmitted through the SPI bus. After the data detected by the monitoring module is transmitted to the microprocessor, the microprocessor generates a three-dimensional motion posture model after Kalman filtering noise reduction and LSTM neural network analysis and prediction, realizing real-time monitoring of the elderly's body posture and prediction of future center of gravity deviation trends, triggering anti-fall response in advance. The data collected by the sensor may be subject to external interference and generate noise. The microprocessor uses the Kalman filter algorithm to process the data, reduce noise interference, and improve the accuracy and reliability of the data. The microprocessor combines historical gait data and uses the LSTM neural network to predict the center of gravity deviation trend of the elderly within the next 200ms, predict the risk of falling in advance, provide a basis for timely adjustment of the drive current, and improve the accuracy of the judgment.

[0063] The control module controls the local viscosity change of the shear thickening fluid in the microcapsule and the local deformation of the shape memory alloy according to the three-dimensional motion posture model to change the wearer's posture and restore the wearer to balance.

[0064] The positioning module and communication module are integrated into the bionic muscle module. The positioning module obtains the wearer's location information in real time, and the communication module is used to send the location information to the guardian's mobile terminal in a timely manner.

[0065] Alarm module: When the wearer falls, the alarm module triggers an alarm and sends an emergency distress signal to the guardian through the communication module.

[0066] The touch screen 4 is arranged on the outside of the bionic muscle module, and is used to display relevant parameters and power, and can adjust the thresholds of various control parameters, such as adjusting the acceleration threshold from 3g to 2g.

[0067] The power supply module is used to power the bionic muscle module, monitoring module, data processing module, control module, positioning module, communication module, alarm module, and touch screen 4. The power supply module is a small, lightweight rechargeable battery (such as a lithium-ion battery) that provides power to the entire system (sensors, processor, etc.). A microcurrent flows from the battery's positive terminal, passes through the control circuit, and is applied to the shape memory alloy. The power supply module is integrated into the touch screen 4, which has a charging port corresponding to the power supply module.

[0068] The working principle of this embodiment is as follows:

[0069] Real-time monitoring:

[0070] Six-axis inertial sensor: This sensor collects the elderly person's three-dimensional acceleration and angular velocity at a frequency of 1kHz, monitoring the body's tilt angle and motion trajectory in real time. For example, when an elderly person leans forward, the sensor detects changes in acceleration in the front-to-back direction and changes in angular velocity along the horizontal axis.

[0071] Piezoelectric fiber array: Detects localized pressure distribution around the waist and identifies the direction of the elderly person's center of gravity shift. For example, when the elderly person's center of gravity shifts to the left, pressure on the left side of the waist increases. The piezoelectric fiber sensor detects this change and transmits a signal to the microprocessor.

[0072] LiDAR micromodule: Based on the TOF principle, it scans the height of ground obstacles and predicts terrain risks. For example, if a step appears in front of an elderly person, the LiDAR micromodule detects the height and distance of the step and transmits the data to the microprocessor.

[0073] Impedance sensor: This monitors the bionic muscle module's deformation resistance in real time, providing a basis for dynamically adjusting the drive current. For example, when the bionic muscle module is subjected to pressure, the impedance sensor detects the change in deformation resistance and feeds the signal back to the microprocessor.

[0074] Data processing and analysis:

[0075] Kalman filtering for noise reduction: After receiving data from various sensors, the microprocessor uses a Kalman filter algorithm to reduce noise, eliminating interference and improving data accuracy and reliability. For example, Kalman filtering removes noise from the acceleration and angular velocity data collected by the six-axis inertial sensor, resulting in more accurate acceleration and angular velocity estimates.

[0076] LSTM neural network prediction: The microprocessor combines historical gait data with an LSTM neural network to predict the trend of the elderly person's center of gravity shift within the next 200ms, thereby predicting the risk of falling. For example, by analyzing the elderly person's walking posture and gait patterns over a period of time, it can predict whether the elderly person's center of gravity will shift further in the future.

[0077] Response and Execution:

[0078] Triggering the response of shape memory alloy and shear thickening fluid: When the microprocessor determines that the elderly person is at risk of falling, such as when the acceleration exceeds 0.5g or the pressure suddenly changes, the corresponding control instructions will be generated. On the one hand, the drive circuit outputs a microcurrent to the shape memory alloy module, heating the nickel-titanium alloy wire, triggering its contraction, and driving the elastic fabric to generate lateral tension; on the other hand, the hardening degree of the shear thickening fluid is controlled, so that its viscosity increases in millisecond response, the local hardness increases, and a rigid support structure is formed. For example, when the elderly person's body leans to the left, the bionic muscle module on the left will quickly harden and contract, generating a lateral pull to the right, pulling the elderly person's center of gravity to the right, and returning the center of gravity to a balanced position.

[0079] The bionic muscle modules provide support and tension: The contraction of the shape memory alloy and the hardening of the shear-thickening fluid enable the bionic muscle modules to quickly form localized rigid support, preventing further deviation of the elderly person's center of gravity. The curved support bars, designed with glass fiber-reinforced polyurethane and mimicking the bionic curvature of the spine, synergistically generate anti-torsional torque, further enhancing the support effect. For example, when the elderly person twists their body, the curved support bars work in conjunction with the shape memory alloy and shear-thickening fluid modules to resist the torque generated by the twisting body.

[0080] Alarm and positioning:

[0081] The alarm module activates: If an elderly person falls or is in a dangerous condition, the alarm module immediately sends a distress signal to pre-set emergency contacts, including the elderly person's location, time of fall, and relevant health data. For example, if an elderly person falls, the alarm module sends a text message and location information to their children's mobile phones via the mobile network, and simultaneously calls the emergency contact number.

[0082] The positioning module provides location information: The positioning module obtains the elderly person's location information in real time and provides it to emergency contacts and rescue personnel when an alarm is triggered. For example, through GPS positioning, rescue personnel can accurately locate the elderly person and provide timely assistance.

[0083] Synergy

[0084] Monitoring and enforcement coordination:

[0085] A six-axis inertial sensor, piezoelectric fiber array, and LiDAR micromodule monitor the elderly person's posture and environmental information in real time, providing accurate data support to the microprocessor. Based on this data, the microprocessor determines the elderly person's risk of falling and promptly triggers the shape memory alloy and shear thickening fluid modules to respond. For example, if the six-axis inertial sensor detects an excessively large tilt angle and the piezoelectric fiber array detects uneven pressure distribution around the waist, the microprocessor determines that the elderly person is unbalanced and immediately triggers the shape memory alloy and shear thickening fluid modules to adjust the elderly person's posture and prevent a fall.

[0086] Execution module collaboration:

[0087] The shape memory alloy module and the shear thickening fluid module work together to provide active and passive support and protection. The shape memory alloy contracts to generate lateral tension, actively adjusting the elderly person's body posture; the shear thickening fluid quickly hardens when under pressure, forming a rigid support structure that passively prevents the elderly person's center of gravity from shifting further. For example, if an elderly person falls forward, the shape memory alloy module quickly contracts, driving the elastic fabric to generate backward tension, while the shear thickening fluid module quickly hardens in front of the waist, providing support and jointly preventing the elderly person from falling forward.

[0088] Alarm and positioning coordination:

[0089] The alarm module and positioning module work together to ensure that if an elderly person falls or is in danger, emergency contacts receive a distress signal and accurately locate the elderly person. For example, if an elderly person falls outdoors, the alarm module immediately sends a distress message to their children, while the positioning module provides the elderly person's real-time location information, allowing children to quickly find the elderly person and provide assistance.

[0090] Overall synergy:

[0091] Data is transmitted between modules via the SPI bus. The microprocessor, acting as the core control unit, coordinates the operations of the modules to implement intelligent fall prevention. For example, when an elderly person approaches a staircase, the LiDAR module detects the stair's height and sends data to the microprocessor. The microprocessor analyzes the data, triggering the alarm module to issue a voice alert to the elderly person and simultaneously adjusting the support strength of the shape memory alloy and shear thickening fluid modules to help the elderly person safely navigate the staircase.

[0092] In this embodiment, the fall risk state includes the initial state stage, the unbalanced state stage, the ground contact state stage, and the ground contact balanced state stage. The specific detection indicators and corresponding solutions are as follows:

[0093] 1. Initial stage

[0094] Response indicators

[0095] Acceleration: The six-axis inertial sensor detected that the elderly person's body acceleration was within the normal range, generally 0.1g-0.5g, indicating that the elderly person's body did not experience abnormal acceleration or deceleration.

[0096] Angular velocity: Angular velocity is usually between 10° / s and 30° / s, reflecting slight adjustments in the elderly's body posture and belonging to slow rotation within the normal range.

[0097] Pressure distribution: The piezoelectric fiber array detected that the pressure distribution in various areas of the waist was relatively uniform, and the pressure difference between adjacent areas was less than 10%, indicating that the center of gravity of the elderly person's body was in a stable state without obvious deviation.

[0098] Duration: The elderly person's body posture remains stable, and the above indicators remain within the normal range for more than 1 second, further confirming that the elderly person is in the initial state.

[0099] Response plan:

[0100] A preload instruction is sent to the bionic muscle module in advance to put the fluid microcapsule into a critical shear state. Based on the motion trajectory of the previous 0.2 seconds, the LSTM model predicts the possible imbalance direction in the next 0.5 seconds and adjusts the module pre-pressure distribution.

[0101] 2. Imbalanced stage

[0102] Response indicators

[0103] Acceleration: The six-axis inertial sensor detects that the elderly person's body acceleration is within the normal range, generally 0.5g-1g, indicating that the elderly person's body may be accelerating and tilting or losing balance.

[0104] Angular velocity: Angular velocity is usually between 30° / s and 60° / s, reflecting the rapid changes in the elderly's body posture, which may be caused by the body beginning to twist or tilt.

[0105] Pressure distribution: The piezoelectric fiber array detected a significant increase in pressure in a certain area of ​​the waist, and the pressure difference between adjacent areas exceeded 20%, indicating that the center of gravity of the elderly person's body had shifted.

[0106] Duration: The elderly person's body posture becomes abnormal, and the above indicators continue to change within 0.2s-0.5s, indicating that the elderly person is in an unbalanced state.

[0107] Response plan:

[0108] The microprocessor determines that the elderly person is in an unbalanced state, analyzes the cause and severity of the imbalance, determines the urgency of the response measures, and predicts the possible direction of fall.

[0109] The control module immediately outputs a microcurrent to the shape memory alloy module, triggering its contraction. This in turn generates lateral tension in the 3D knitted gradient fabric, adjusting the elderly person's posture. Simultaneously, the hardness of the shear-thickening fluid microcapsules is controlled to provide localized support. Impedance sensors are activated to monitor deformation resistance in real time, dynamically adjusting the drive current to ensure effective support. The alarm module then triggers a warning message to the caregiver.

[0110] 3. Touchdown phase

[0111] Response indicators

[0112] Acceleration: The six-axis inertial sensor detected a sharp increase in the elderly person's body acceleration, reaching 2g-3g, indicating that the elderly person's body may be accelerating and falling toward the ground.

[0113] Angular velocity: Angular velocity is usually between 60° / s and 100° / s, reflecting the rapid rotation of the elderly's body posture, which may be caused by a flip after the body loses balance.

[0114] Pressure distribution: The piezoelectric fiber array detected a sharp increase in pressure in the area where the waist contacts the ground, exceeding 100 kPa, indicating that part of the elderly person's body had touched the ground.

[0115] Duration: The elderly person's body posture becomes abnormal, and the above indicators change rapidly within 0.1s-0.2s, indicating that the elderly person is in a ground contact state.

[0116] Response plan:

[0117] The control module adjusts the shape memory alloy and non-Newtonian fluid modules to provide appropriate support and cushioning according to the landing point and the direction of the fall. At the same time, it activates the alarm module to send an emergency distress signal to the guardian. If the elderly person is conscious, they can confirm whether further rescue is needed through voice or action, and the system will feedback this information to the guardian.

[0118] 4. Touchdown balance stage

[0119] Detection indicators:

[0120] Acceleration: The six-axis inertial sensor detects that the acceleration of the elderly person's body gradually decreases and stabilizes, returning to 0.1g-0.5g, indicating that the elderly person's body has stopped accelerating and reached a relative static state.

[0121] Angular velocity: The angular velocity is usually between 10° / s and 30° / s, reflecting a slight adjustment in the elderly's body posture, indicating that the elderly's body has stopped rotating and reached a state of equilibrium.

[0122] Pressure distribution: The piezoelectric fiber array detected that the pressure distribution in various areas of the waist gradually became uniform, and the pressure difference between adjacent areas was less than 10%, indicating that the center of gravity of the elderly person's body had regained a stable state.

[0123] Duration: The elderly person's body posture tends to be stable, and the above indicators remain within the normal range for more than 1 second, indicating that the elderly person is in a ground-touching equilibrium state.

[0124] Response plan:

[0125] The microprocessor fine-tunes the shape memory alloy and non-Newtonian fluid modules to provide appropriate support to help the elderly maintain balance or prepare to stand up again. At the same time, the alarm module sends the elderly status information to the guardian, informing the guardian that the elderly is in a balanced state and does not require emergency rescue. If the elderly needs assistance to stand up, the system can provide guidance through vibration or sound prompts.

[0126] In summary, the present invention realizes real-time monitoring of the wearer's body posture and surrounding environment through the mutual cooperation between various modules, adjusts the wearer's body posture in real time, provides active and passive support protection, prevents falls, effectively protects the safety of the elderly, and improves the quality of life and independence of the elderly.

[0127] In the description of the present invention, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention.

[0128] Those skilled in the art can make various other corresponding changes and deformations based on the technical solutions and concepts described above, and all of these changes and deformations should fall within the scope of protection of the claims of the present invention.

Claims

1. An intelligent anti-fall belt, characterized in that: include: A bionic muscle module, the bionic muscle module being in the shape of a waist belt, comprising a 3D knitted gradient fabric layer (1), a shear thickening fluid microcapsule array layer (2), and a shape memory alloy support mesh layer (3) arranged sequentially from the inside to the outside; A monitoring module, which is used to monitor the wearer's body posture information and surrounding environment information; a data processing module, wherein the data processing module processes the body posture information and surrounding environment information to generate a three-dimensional motion posture model; a control module, wherein the control module controls the local viscosity change of the shear thickening fluid in the microcapsule and the local deformation of the shape memory alloy according to the three-dimensional motion posture model to change the posture of the wearer and restore the wearer's balance; A power supply module is used to supply power to the bionic muscle module, the monitoring module, the data processing module and the control module.

2. The intelligent anti-fall belt according to claim 1, characterized in that: The 3D knitted gradient fabric layer (1) comprises a waist middle region, waist side regions and edge regions, wherein the waist middle region is knitted with yarn having a linear density greater than 22.2 tex, the waist side regions are knitted with yarn having a linear density between 8.3 and 22.2 tex, and the edge regions are knitted with yarn having a linear density less than 8.3 tex.

3. The intelligent anti-fall belt according to claim 2, characterized in that: The microcapsules are arranged in a hexagonal honeycomb structure and interconnected by microchannels.

4. The intelligent anti-fall belt according to claim 3, characterized in that: The shape memory alloy support mesh layer (3) is embedded with glass fiber reinforced polyurethane material and forms an arc-shaped support bar with a bionic curvature of the spine.

5. The intelligent anti-fall belt according to claim 1, characterized in that: The monitoring module includes a six-axis inertial sensor, a piezoelectric fiber array, a laser radar micromodule and an impedance sensor; The six-axis inertial sensor is provided on the bionic muscle module and is used to collect the three-dimensional acceleration and three-dimensional angular velocity of the wearer's body; The piezoelectric fiber array is embedded in the 3D knitted gradient fabric layer (1) and is used to detect local pressure distribution and identify the direction of the wearer's center of gravity deviation; The laser radar micro-modules are distributed around the bionic muscle module to scan the height of ground obstacles, predict terrain risks, and promptly detect potential danger signals in the wearer's surrounding environment; The impedance sensor is arranged outside the shear thickening fluid microcapsule, and the impedance sensor detects the deformation resistance of the bionic muscle module in real time; The data processing module determines whether the wearer is at risk of falling based on the three-dimensional acceleration and three-dimensional angular velocity, the center of gravity offset direction, the potential danger signal and the deformation resistance; If so, the control module dynamically adjusts the driving current to control the shear thickening fluid to change viscosity and the shape memory alloy to contract, ensuring that the bionic muscle module provides appropriate supporting force.

6. The intelligent anti-fall belt according to claim 5, characterized in that: The monitoring module also includes a temperature compensation module, which is closely attached to the shear thickening fluid microcapsule array and the shape memory alloy, and is used to monitor the ambient temperature and the operating temperature of the bionic muscle module in real time, and feed the temperature data back to the data processing module. The data processing module adjusts the driving current according to the temperature data to ensure the stability of the viscosity of the shear thickening fluid.

7. The intelligent anti-fall belt according to claim 1, characterized in that: It also includes a positioning module and a communication module. The positioning module and the communication module are integrated into the bionic muscle module. The positioning module obtains the wearer's location information in real time, and the communication module is used to send the location information to the guardian's mobile terminal in a timely manner.

8. The intelligent anti-fall belt according to claim 7, characterized in that: It also includes an alarm module. When the wearer falls, the alarm module triggers an alarm and sends an emergency distress signal to the guardian through the communication module.

9. The intelligent anti-fall belt according to claim 1, characterized in that: It also includes a touch screen (4), which is arranged on the outside of the bionic muscle module, and the power supply module is integrated into the touch screen (4).

10. The intelligent anti-fall belt according to any one of claims 1 to 9, characterized in that: The shear thickening fluid comprises, by mass percentage, 38%-45% of silicon dioxide nanoparticles, 50%-60% of polyethylene glycol base liquid, 1%-3% of boron carbide nanosheets, and 0.5%-1% of a boron-containing ester bond compound.

Images