32 results about "Gait types" patented technology

A landing shock absorbing device 18 disposed in a foot mechanism 6 of a leg of a robot, wherein an inflatable bag-like member 19 (variable capacity element) is provided at a bottom face side of the foot mechanism 6. The bag-like member 19 is constructed of an elastic material such as rubber. The air in atmosphere may flow into and out of the bag-like member 19 by inflow/outflow means 20 equipped with a solenoid valve 27, and the like. In a lifting state of the foot mechanism 6, inflow of the air into the bag-like member 19 is controlled, thereby controlling the final height of the bag-like member 19 in an inflated state to the height in response to a gait type of the robot. While properly reducing an impact load during a landing motion of the leg of a legged mobile robot depending on the gait type of the robot, stability of a posture of the robot may easily be secured, resulting in allowing a configuration to be lighter in weight.

The invention discloses a gait type identification method based on a three-axis acceleration sensor and a neural network. The method specifically comprises steps as follows: step 1), establishing a database of gait acceleration signals; step 2), performing the segmentation stage of the signals in the corresponding period; step 3), removing a gravity factor; step 4), performing the gait feature extraction stage; step 5), performing gait presorting stage; step 6), performing dimensionality reduction operation of a gait feature set; and step 7), performing specific gait identification stage. According to the method, gait features are screened with a staged MIV (mean impact value) method, the gait type identification work is performed in combination of a BP (back propagation) neural network, the extracted features are taken as input independent variables of the neural network, six gait types of sitting, standing, walking in a low speed, walking in a high speed, going upstairs and going downstairs are effectively identified sequentially through the gait presorting stage and the specific gait identification stage, and the method can have higher accuracy and reliability through enlarging of a gait data capacity range and the optimized design of the neural network.

The invention discloses a support vector machine-based pedestrian gait classifying system and a support vector machine-based pedestrian gait classifying method. The system comprises a data acquiring module, a data processing module and an SVM (Storage Virtualization Management) module, wherein the SVM module is provided with a storage medium; the data acquiring module acquires gait training data and transmits the gait training data to the data processing module to be processed; the data processing module outputs the input quantity of the acquired gait training data to the SVM module to be studied to obtain an SVM classifier which is then stored in the storage medium; during real-time test, after real-time gait information is acquired in real time by the data acquiring module, data processing is preformed by the data processing module to acquire the input quantity of the test data; the input quantity of the test data is classified by the SVM module according to the SVM classifier to obtain real-time gait type. A static interval in a pedestrian moving process can be precisely detected by the system and the method, and the positioning precision is improved.

The invention relates to an auxiliary motion system and a lower limb exoskeleton control method. The auxiliary motion system comprises a lower limb exoskeleton supporting device and a data acquisitiondevice and a control device which are arranged on the lower limb exoskeleton supporting device, wherein the lower limb exoskeleton supporting device comprises a shank supporting part, a thigh supporting part and a hip supporting part; the data acquisition device comprises a first sensor arranged at the junction of the hip supporting part and the thigh supporting part and a second sensor arrangedat the shank supporting part, and the first sensor and the second sensor are used for collecting gait data and walking data which are related to human motion; the control device is arranged on the hipsupporting part, and is used for acquiring the gait data and walking data which are collected by the data acquisition device and determining a current gait type according to the gait data and a gaitclassification rule so that the real-time physical state of the patient can be analyzed according to the gait type and the walking data under the corresponding gait type.

Disclosed are an apparatus and a method for gait type classification using a pressure sensor of a smart insole, which are capable of classifying pieces of gait data having various variances using only a pressure sensor. The apparatus for gait type classification includes a gait data measuring part configured to measure pieces of gait data using a pressure sensor, a pre-processor configured to define a section of a unit step in all the pieces of gait data, divide the pieces of gait data for each unit step, and normalize the pieces of divided gait data to equalize lengths of the pieces of divided gait data, and a feature extractor configured to extract features suitable for gait type classification from the pieces of pre-processed gait data, and a gait type classifier configured to receive the extracted features as an input and determine and classify a final gait type.

The invention provides a human body gait analysis-based system of safety door and a control method thereof. The gait safety door provided by the application is equipment which collects and recognizesgait features of human bodies, and controls door leaf opening and closing according to the gait features. According to the system of the safety door, on the one hand, multi-dimensional human body gaitrecognition technology is employed for identification of the gait features, and the technical problems of low recognition result accuracy, poor robustness, high realization difficulty and the like existing in single-dimensional gait recognition of videos, radar echoes or the like in the prior art are solved; and on the other hand, aggregation of passer gait types is realized on the basis of the multi-dimensional human body gait features, then suitable opening duration is set for the different gait types, and intellectualization and humanization of automatic door opening and closing of the safety door are improved.

The embodiment of the invention provides a gait recognition model building method based on myoelectric signals, a recognition method and a device. The model building method comprises the following steps of collecting the myoelectric signals; reducing the noise; adding a class tag and extract the following EMG signal characteristics: slope change rate, Willison amplitude, logarithm of variance, waveform length, and characteristics DB7-MAV; calculating the DBI index and SCAT index and obtaining the comprehensive evaluation results. The comprehensive evaluation result are randomly divided into atraining sample group and a test sample group according to a predetermined proportion, and input them into the LightGBM model for training and testing. The parameters in LightGBM model are adjusted according to the error of training set and test set, and grouped, trained, tested and adjusted repeatedly until the error of model test results accords with the data model of predetermined standard, andthe corresponding relationship between human gait type and comprehensive evaluation results is stored in the data model. The embodiment of the invention can efficiently and accurately establish a data model, and the gait recognition rate is high and the recognition result is more reliable.

A tunable rigidity insole with interchangeable stiffeners includes an arch pad main body and three rigid stiffeners. The arch pad main body includes a set of first to third engaging holes, and at least one or two of these three rigid stiffeners will be selected to assemble into the engaging holes on the arch pad main body. The three rigid stiffeners provide supports to lateral longitudinal, central and medial longitudinal arch portions respectively. The first, second and third rigid stiffeners have at least two engagement members for each stiffener, and the engagement members have engagement extensions with a partial length component toward another engagement extensions at the end of stiffeners thereof respectively. The engagement members engage with the arch pad main body corresponding to the engaging holes respectively. By selecting and assembling different stiffeners, the present invention can have different rigidities of arch supports to match with various foot biomechanics and gait types in order to provide different arch supports thereto properly.

The invention provides a gait control method, comprising: providing gait model and reference information; collecting original gait information and judging gait type according to the gait model; collecting the state information of the booster module and converting the state information into the parameter information; invoking the reference information and the parameter information to compare according to the gait type; and sending an adjustment instruction to the booster module so that the parameter information conforms to the reference information. The gait model of the gait control method ofthe present invention includes a foot-flattening model, heel off-ground model and toe off-ground model, at the stage when the wearer needs power assistance or adjustment, the comparison basis is provided, and the reference information is combined to enable the gait control method to realize the control of the power assistance module without re-determining the gait period, thereby avoiding the problem of tracking speed and precision degradation caused by continuously re-determining the gait period. The invention also provides a gait control system for realizing the gait control method.

The invention discloses a planning method for a foot end track of a rhythm gait of a hexapod robot. The method comprises the following steps: determining a land occupation coefficient and a swing period number in one gait period according to three rhythm gait types; planning a walking stride and a single step length of the rhythm gait; planning a hexapod robot foot end motion track interpolation function based on a trigonometric function and an S-shaped function; planning an instantaneous step length interpolation function expression of a swing phase and a support phase; and solving the instantaneous coordinates of the foot end of the hexapod robot relative to a machine system. According to the rhythm gait foot end track planning method, parameters can be adjusted in real time, a smooth foot end motion track can be obtained, and the method is suitable for all-dimensional motion of rhythm gaits of a hexapod robot under different terrains.

The invention provides a lower limb prosthesis hierarchical control system and method based on healthy side leg multi-source information, which comprises a man-machine system module, a sensing system module, a signal preprocessing module and a hierarchical controller. The sensing system module is mounted on one side of a healthy leg of a human body of the man-machine system module; the hierarchical controller is composed of a top-layer controller module, a middle-layer controller module and a bottom-layer controller module. The input end of the signal preprocessing module is the signal output of the sensing system module, and the output of the signal preprocessing module is divided into two parts which are respectively connected with the top-layer controller module and the middle-layer controller module; the output of the top-layer controller module is connected with the middle-layer controller module; the output of the middle-layer controller module is connected with the bottom-layer controller module; and the bottom-layer controller module and the prosthesis side of the man-machine system module perform bidirectional interaction. According to the invention, the gait discrete switching of different gait types in actual use can be realized, and the walking speed can be continuously adjusted in real time according to the human body intention in the same gait period.

The invention discloses a human abnormal gait recognition method based on a smart phone. According to the method, human gait data can be effectively collected through the smart phone, the related feature information of different gait types of a human body is extracted, and the classification and recognition of different abnormal gait types are achieved. The limitation of a traditional abnormal gait analysis and detection method is overcome.

The invention discloses a method and a device for waking up an intelligent device, which relate to the technical field of artificial intelligence and can solve the problem that in different application scenarios, the recognition strategies for waking up voices are the same, the flexibility is poor, and the use requirements cannot be met. The method of the present invention includes: collecting the current gait information of the user; using a preset gait recognition model to identify the gait type represented by the current gait information; determining the wake-up speech recognition strategy according to the gait type; when receiving When the voice wake-up word input by the user is detected, the voice wake-up word is recognized according to the wake-up voice recognition strategy, and the smart device is woken up based on the recognition result. The present invention is mainly applicable to the scenario where the smart device is awakened by voice.

The invention is suitable for the technical field of data analysis of virtual reality, and provides a virtual character motion synchronization method and terminal equipment, and the method comprises the steps: obtaining first motion data and second motion data in an inertial MEMS sensor; wherein the inertial MEMS sensor is bound to the ankle part of a real person, the first motion data are acceleration data, and the second motion data are angular velocity data; analyzing the start-stop state of the real person according to the second motion data, and obtaining start-stop information of the real person; when the real person is in a motion state, analyzing a current gait type based on the current frame according to the first motion data and the second motion data through a decision tree algorithm, and calculating leg motion data based on the current gait type; and according to the start-stop information, the current gait type and the leg motion data, synchronizing the motion of the real character and the motion of the virtual character. According to the method, switching delay caused by mixed operation of various data can be avoided.

In a transient ischemic attack (TIA) alerting device, a motion sensor (24) is configured to attach to or be worn by a subject. A wearable electronic data processing device (10) includes a speaker (14), a microphone (16), a radio transmitter (26), and an electronic processor (40). The processor is programmed to perform a TIA alerting method including: detecting a TIA-symptomatic gait type by processing subject motion data acquired by the motion sensor; responsive to detecting the TIA-symptomatic gait type, executing a TIA assessment questionnaire (70) by outputting questions using the speaker and receiving spoken responses using the microphone; determining a TIA assessment based at least on the spoken responses to the questions of the TIA assessment questionnaire; and conditional on the TIAassessment indicating a possible TIA, outputting a TIA alert radio signal using the radio transmitter.