56 results about "Step count" patented technology

A method includes: determining a motion pattern of a user after an initiation of a walking activity; detecting one or more false steps and a gait abnormality associated with the user, based on the motion pattern; detecting an arm swing angle of the user and a leg swing angle of the user, based on the motion pattern and the walking activity; estimating a first variation in the arm swing angle and a second variation in the leg swing angle in the walking activity; calculating, using a machine learning (ML) model of a plurality of ML models, a compensation value associated with the one or more false steps, based on a combination of the first variation and the second variation, and a height of the user; and determining a step count of the user, based on the calculated compensation value and an initial step count of the user.

The invention discloses a method and a system for accelerometer and gyroscope- based step counter for virtual reality navigation The method (300) includes capturing (302) a movement data of a user (106) wearing a head mounted display (HMD) device (102), filtering (304) the movement data captured using a sensor (206) to attenuate a noise generated along with the movement data to get a filtered data and analysing (306) the filtered data to determine if the filtered data is within a predefined threshold. The method further includes calculating (308) a step count if the filtered data is within the predefined threshold and increasing (310) a virtual step based on the step count calculated to mirror a real-world movement of the user (106) in a virtual environment.

Activity level and fall detection using accelerometer data is described. In one or more implementations, measurements of a user generated by a wearable monitoring device during an observation period are obtained, the measurements including accelerometer data. Physical steps taken by the user are detected based on peaks in the accelerometer data above a threshold, and a step count is generated based on the detected physical steps within predetermined time epochs. Activity level classifications of the user for the predetermined time epochs are generated based on the step count. The step count and the activity level classification for the predetermined time epochs may then be output, such as a notification or in a user interface. Fall predictions may be generated and output by processing the accelerometer data using machine learning models trained to correlate patterns in accelerometer data to fall events.

The invention discloses a step counting method and device of a hearing aid system, a hearing aid, a medium and a product, and relates to the technical field of hearing aids, the disclosed step counting method of the hearing aid system is applied to the hearing aid, the hearing aid comprises a gyroscope and a triaxial accelerometer, and the step counting method of the hearing aid system comprises the following steps: obtaining first data through the triaxial accelerometer, the first data is data collected by the triaxial accelerometer, and the second data is data collected by the gyroscope; taking data corresponding to the z axis in the first data as first target data; detecting a peak value in the first target data, and taking an acquisition moment corresponding to the peak value as a target moment; and taking data corresponding to the target moment in the second data as second target data, and calculating the step number according to the second target data. The technical scheme of the invention aims to solve the technical problem of how to improve the accuracy of the step counting function in the hearing aid.

A controlling method of an electronic apparatus, the method comprising obtaining main motion data and sub motion data, obtaining synthetic data by combining the main motion data and the sub motion data, obtaining a threshold value based on a magnitude of a signal waveform of the synthetic data and a running mean of the synthetic data, identifying a plurality of critical points in the synthetic data based on the threshold value, identifying signal patterns, based on the plurality of critical points, in each axis of a plurality of axes in the main motion data of a 3-Dimension (3D) coordinate system, obtaining at least one similarity in the signal patterns based on a plurality of inter-axis features extracted from the synthetic data, obtaining a degree of symmetry between each axis of the plurality of axes based on the at least one similarity, and obtaining a user's movement information based on the degree of symmetry and the synthetic data.

Improve the accuracy of step counting. [Solution] The data acquisition unit 101 acquires 3-axis acceleration data for 3 axes output by a 3-axis acceleration sensor attached to the user. The step count estimation unit 103 estimates the user's step count based on the composite acceleration data obtained from the 3-axis acceleration data. The arm swing count estimation unit 104 estimates the user's arm swing count based on specific axis acceleration data from the 3-axis acceleration data that corresponds to the direction in which the user's arm is swung. The step count measurement unit 107 measures the user's step count by switching between the user's step count estimated by the step count estimation unit 103 and the user's arm swing count estimated by the arm swing count estimation unit 104, according to a predetermined standard.

An object of a system according to an embodiment is to improve a user's walking experience by automatically generating music according to a walking speed.SOLUTION: A system includes a step counting part, a BPM determination part, a musical piece generation part, and a tempo adjustment part. The step counting unit measures a walking speed using a step counting function of the smartphone. The BPM determining unit determines the BPM based on the data measured by the step counting unit. The music generation unit generates music on the basis of the BPM determined by the BPM determination unit. The tempo adjusting unit increases or decreases the BPM according to the user's desire.SELECTED DRAWING: Figure 1

To provide a user with a program capable of increasing motivation to perform a prescribed life behavior.SOLUTION: A computer is made to function as a reception part (an operation information reception part 11, a step count reception part 14) for receiving information showing that a user performs a prescribed life behavior, a point management part 15 for increasing and decreasing point values on the basis of time series data related to a time receiving information or / and contents of the information when the reception part receives the information, a point determination part 16 for determining whether or not the point values reach a prescribed value, and a display control part 21 for displaying a screen on a display 5 and changing the screen when the point determination part 16 determines that the point value has reached the prescribed value.SELECTED DRAWING: Figure 2

A heart rate monitoring method based on multiple physiological parameters comprises the steps that monitoring physiological parameters are collected in real time, time information and the monitoring physiological parameters are bound in sequence, and the monitoring physiological parameters comprise heart rate data; according to the method, the multiple steps of synchronously collecting the step number and the respiration number according to the preset period, calculating and obtaining the step frequency data and the respiration frequency data of the unit time and the like are included, data correction is conducted on the heart rate monitoring result through fusion calculation of the multiple physiological parameters and the heart rate parameters of the personalized object, the data fusion and precision are improved, and the accuracy of the heart rate monitoring result is improved. And efficient health monitoring is realized.

This invention discloses an indoor positioning method based on LTE signal fingerprint matching and nearest neighbor observations constrained by PDR (Progressive Directional Recognition), belonging to the field of indoor navigation and positioning technology. The method first performs step count detection, step length estimation, and heading estimation based on MEMS sensor output to obtain PDR positioning results. Then, it uses the PDR positioning results and an indoor map to estimate LTE signal propagation model parameters online, quickly constructing a fingerprint database, and obtaining location observations through fingerprint matching. Simultaneously, it utilizes the peak variation pattern of the LTE signal RSRP (Regressive Range Recognition Point) to identify antenna positions using peak detection and threshold constraints, extracting nearest neighbor position, step length, and heading observations. Finally, it employs unscented Kalman filtering to fuse the PDR results and the aforementioned observations in different scenarios. This invention requires no prior data, can adapt to changes in environment and equipment, and combines low cost with high accuracy, making it suitable for indoor pedestrian positioning.

A system is provided.SOLUTION: A system including means for recording an image of a meal with a camera, means for analyzing meal contents by image recognition, means for calculating ingested nutrients on the basis of an analysis result, means for storing the analysis result in a cloud server, means for measuring the number of steps, means for transmitting step count data to the cloud server, means for calculating consumed calories on the cloud server, means for comparing ingested calories and consumed calories and generating advice, and means for notifying a user of the generated advice.SELECTED DRAWING: Figure 1

The application discloses a kind of based on step prediction's stepper motor acceleration-deceleration curve parameter table generation method and multi-motor motion control method, wherein the above-mentioned method includes: obtaining the basic parameters of motor acceleration-deceleration process;Typical S-type acceleration-deceleration curve of motor is compensated to obtain the S-type speed curve of motor running speed;Integral calculation is carried out to S-type speed curve and obtains S-T function;S-T function is obtained by solving the inverse;According to the running step and motor differential mode, calculate microstep step;Then, combined with total distance, the microstep running distance table of motor after equal-distance division is calculated and obtained;Microstep running distance table and T-S function are combined, and the microstep running time node table of motor is calculated;Substitute S-type speed curve of motor running speed and calculate to obtain the speed table of each microstep moment;Corresponding acceleration-deceleration curve parameters are generated using each speed value in microstep speed table.The technical problem that classical table lookup method does not consider the change of timer period is solved.

1. The name of the product of this design: Wrist-type student ID card (KXS57). 2. Purpose of this design product: This design product is mainly used for wrist-type student ID cards for making calls, counting steps, heart rate and blood oxygen health monitoring, and positioning. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the key points of the design: Design 1 Stereoscopic drawing 1. 5. Designate Design 1 as the base design.

The invention relates to a device (V) for monitoring the health of an animal (1), wherein the device (V) comprises at least one collar or harness (2) with at least one detection unit (3) and an evaluation unit (4) communicating with the detection unit (3), characterized in that - the detection unit (3) comprises at least one motion sensor (3.1) and a communication unit (3.5), - wherein the motion sensor (3.1) is designed to count individual steps of the animal (1) and to transmit detected step count information via the communication unit (3.5) to the evaluation unit (4) for evaluation of the detected step count information.

The invention discloses a poultry health state intelligent diagnosis method based on dynamic step counting, which comprises the following steps: installing a step counting foot ring on a leg of poultry to be monitored to obtain the step number of the poultry at regular time, and obtaining the body temperature of the poultry through a wing label; constructing a poultry database; generating a breeding environment big data thermodynamic diagram based on a preset grid size on the basis of the individual positions, the exercise amount, the feed consumption, the environmental parameters and the poultry health state of the poultry, constructing a poultry group density distribution prediction model by using a hierarchical learning network, and predicting poultry group density distribution; and in combination with the birth days of the poultry and the growth and development rules of the poultry, constructing an intelligent diagnosis model of the exercise amount, the feed dosage, the environmental parameters and the abnormal state by using a graphic space-time network, and predicting the health state of the poultry. The poultry health detection precision and accuracy can be effectively improved, and the poultry health condition can be visually reflected.

The application discloses a wearable motion monitoring device for Parkinson's disease, which comprises an assembly body, a detection bracelet and a step counting foot ring, an external wearable clothing body of the assembly body, a sensor body arranged on the clothing body, the detection bracelet and the step counting foot ring are sleeved to the external assembly body, a connecting assembly is arranged between the sensor body and the clothing body, the connecting assembly is used for fixing the sensor body, a plurality of monitoring assemblies are arranged at joints of the clothing body respectively, the monitoring assembly comprises a bearing box, an air bag sleeve is arranged in the bearing box, an air pressure detector is fixedly installed in the bearing box, a transmission assembly is arranged on the bearing box, and a mounting assembly is arranged between the bearing box and the clothing body. According to the setting mode of the clothing body and the monitoring assembly, when a patient's limb moves, the transmission assembly can cooperate with the bearing sleeve to extrude the air bag sleeve, so that the air pressure detector detects the air pressure change in the air bag sleeve, and the state of the patient's limb movement is recorded.

A system for enhanced analysis of activity signals from on-body devices for tracking activity of a plurality of clinical research subjects is provided. The system may comprise a plurality of on-body devices, each configured to be worn by a separate subject, and each device including an accelerometer and / or a gyroscope configured to generate an activity signal based on body movement of the subject wearing said device. A remote computing device may be configured to filter and decompose the received activity signal to identify an Intrinsic Mode Function ("IMF"), compute an instantaneous energy of the IMF, and count peaks of the IMF having an instantaneous energy that is above a predetermined threshold as steps. The steps derived from subjects that received a health intervention may then be compared against steps derived from subjects that did not receive the health intervention to assess an efficacy of the health intervention.

This system provides walking routes generated based on individual user profiles, promoting enjoyable and efficient exercise. [Solution] A system comprising: a means for registering the user's basic information and hobbies and preferences using a personal information input means; a means for measuring the number of steps based on the user's daily activities using a step counting means; a means for generating individual walking routes using the user's registered information and location information using a generation means; a means for suggesting exercise time based on the user's free time using a scheduling means; a means for awarding points and offering rewards for the user achieving their goals using a reward provision means; a means for displaying advertisements for specific stores to the user on the walking route using an advertisement display means; and a means for aggregating and analyzing the user's behavior information using a data aggregation means.

The application provides a data processing method and device, wherein the data processing method comprises: obtaining to-be-processed data used for counting steps and initial step counting data corresponding to the to-be-processed data, wherein the to-be-processed data comprises at least one to-be-processed sub-data; determining a first step counting parameter and a second step counting parameter corresponding to each to-be-processed sub-data; determining a target state corresponding to each to-be-processed sub-data according to the first step counting parameter and the second step counting parameter corresponding to each to-be-processed sub-data; and determining target step counting data corresponding to the to-be-processed data based on the initial step counting data and the target state corresponding to each to-be-processed sub-data. The target state corresponding to each to-be-determined data in the to-be-processed sub-data is determined, so as to eliminate the false step counting in the to-be-processed sub-data, thereby improving the accuracy of step counting on the to-be-processed data. Compared with a traditional step counting algorithm, the calculation amount is greatly reduced, and the calculation cost is reduced.

This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

The present application discloses a step counting method and device. The step counting method includes: obtaining a first acceleration, a second acceleration, and a third acceleration of three axes of an acceleration sensor in a terminal device within a preset time period, where the first acceleration, the second acceleration, and the third acceleration are perpendicular to each other pairwise in the acceleration direction; determining a motion change amount of the user within the preset time period based on the first acceleration, the second acceleration, and the third acceleration within the preset time period; and determining the number of steps of the user within the preset time period based on the resultant acceleration of the first acceleration, the second acceleration, and the third acceleration and the gravitational acceleration within the preset time period when the motion change amount of the user within the preset time period is greater than or equal to a preset variance threshold.

A system is provided.SOLUTION: A system comprising: means for inputting health check data; means for taking a picture of each meal and inputting contents of the meal; means for transmitting the health check data, meal data, and step count data to a server; means for analyzing the data in the server, evaluating a health condition, and generating an improvement proposal; means for transmitting the generated improvement proposal and recommended store information to a terminal; and means for notifying a user of the improvement proposal displayed on the terminal.SELECTED DRAWING: Figure 1

The invention discloses application software integrating functions of a pedometer and a music player. A user can exchange music VIP rights and interests and single music permission through walking steps. Software comprises four core modules: 1, a step counting module, which is used for collecting steps in real time and supporting a user-defined daily effective step number threshold value (20000 steps at most), and the exceeded part is not accumulated; the music playing module integrates online / local playing, provides VIP exclusive content (no advertisement, lossless tone quality, exclusive album and the like) and a step number exchange single music library, recommends personalized song lists based on a user data algorithm, and plays local music; 3, the step number exchange module is used for presetting exchange rules (for example, the VIP member is exchanged for 30 days by 360 million steps, for example, the single song is downloaded to the local for 1 day and unlimited times by 200 million steps and is played on line for 30 days and unlimited times within a specified time limit), and the user completes step number deduction and right activation through an operation interface. The user interaction module comprises a step number statistics interface, a music playing interface and an exchange interface, supports single-song search, secondary confirmation and multi-device data synchronization, and displays the step number progress and personalized recommendation in real time. According to the method, a'exercise-accumulation-exchange 'closed loop is constructed, a channel for obtaining music rights and interests for free is provided for non-paid users, health exercise behaviors are stimulated, software use stickiness is improved, meanwhile, the music content propagation path is expanded, and the method has innovativeness, practicability and wide market prospects.

The invention relates to a health exercise step counting method and system based on fusion sensor data, and the system comprises a starting and login module which is used for loading a starting page and carrying out the login of a user; the information setting and synchronizing module is used for setting basic information of the user and synchronizing motion data in real time; the exercise step counting module is used for recording the walking step number of the user in real time and uploading the walking step number to the server; the activity management module is used for managing adding, modifying and lottery drawing operations of sports activities; and the ranking and interaction module is used for collecting the step number data of the user and carrying out ranking display. The method has the advantages that multi-sensor data fusion is achieved, the system can more accurately capture the motion state of a user by integrating data of a plurality of sensors (such as an accelerometer and a gyroscope), and the step counting accuracy and reliability are improved.

An object of the present invention is to provide a novel technique capable of predicting an activity amount in consideration of various physical activities in a day.SOLUTION: In order to solve the above problem, the present invention provides a prediction system for predicting an activity amount for one day, the prediction system including a step count management unit and an activity amount prediction unit, wherein the step count management unit acquires a step count of a user, and the activity amount prediction unit calculates a predicted activity amount for one day based on the step count and a prediction means.SELECTED DRAWING: Figure 1

The invention discloses a PDR step counting method assisted by sound, and belongs to the technical field of indoor navigation and localization. Triaxial acceleration and triaxial angular velocity data are collected through an inertial sensor of a smart phone, environmental audio data are collected through a microphone, and synchronization is carried out based on a unified time sequence; identifying the current carrying state of the mobile phone; starting a corresponding audio analysis model according to the carrying state, and extracting a specific acoustic event related to the gait cycle from the environment audio; performing preliminary gait detection on the inertial data, and extracting candidate gait cycles and step numbers; the sound event sequence and the inertial gait sequence are subjected to space-time matching and fusion, step counting correction is achieved through matching verification, missed step compensation and wrong step elimination, and the high-confidence-coefficient step number is output; interference of a single sensor in complex carrying modes and various motion states can be effectively suppressed, step counting accuracy, environmental adaptability and system robustness are remarkably improved, and the method is suitable for PDR positioning of large indoor scenes such as airports and terminals.

The invention discloses an indoor high-precision step counting method and system based on multi-modal inertial navigation data, and the method comprises the following steps: carrying out the multi-modal data preprocessing and adaptive fusion filtering of collected acceleration data and angular velocity data, and obtaining a smooth acceleration signal and a smooth angular velocity signal; based on the two signals, multi-mode cooperative gait recognition is carried out, an effective gait peak value is recognized, and a gait cycle and a real-time stride frequency are calculated; carrying out multi-modal fusion verification on a gait recognition result, and judging an effective movement gait; based on a historical step length library classified according to motion types, step length self-adaptive calibration is carried out according to the real-time step frequency, and a current adaptive step length is obtained; and calculating and outputting indoor motion parameters according to the step number of the effective motion gait and the current adaptive step length. According to the invention, accurate step counting and motion parameter calculation in a human body motion state can be realized in an indoor scene without GPS signals.

The invention belongs to the technical field of intelligent equipment, and particularly relates to a step counting method, a step counting system, a step counting device and a medium applied to a sports equipment use scenario, and the method comprises the following steps: when a user triggers a step counting detection function of an intelligent wearable device, acquiring acceleration waveform data of an arm of the user along a motion main axis direction; the direction of the motion main shaft is at least consistent with the forward-swinging / backward-swinging direction of the arm of the user; identifying a wave crest and a wave trough on the acceleration waveform data by utilizing a wave crest judgment condition and a wave trough judgment condition, and identifying whether the wave crest or the wave trough is effective by utilizing a wave crest effective judgment condition and a wave trough effective judgment condition; and when the effective wave crest or the effective wave trough is identified, adding one to the step number of the user so as to accumulate the total step number of the sports equipment used by the user. According to the method, the characteristic rule between the hand characteristics and the step number change when a user uses similar sports equipment such as an ellipsograph is utilized, so that step counting is carried out by recognizing the wave crest and the wave trough of the acceleration waveform of the arm in the movement main axis direction.

This application discloses a step counting method, apparatus, device, and storage medium. The method includes: acquiring sampling data from i sets of sensors on a target object, where i ≥ 3; constructing a sampling matrix and a unit basis vector based on the sampling data from the i sets of sensors; detecting leg raising and lowering movements of the target object based on the sampling matrix and the unit basis vector; and counting steps on the target object based on the leg raising and lowering movements. This technical solution is not limited to software detection methods and can accurately determine leg raising and lowering movements based on sensor-detected sampling data. It can achieve accurate step counting even when the system is powered off, making step counting highly flexible and reducing system power consumption.

An object of the system according to the embodiment is to accurately grasp the health condition and emotion of the pet and provide appropriate advice to the owner.SOLUTION: A system according to an embodiment includes a data collection unit, a data transmission unit, a data analysis unit, an emotion estimation unit, and an advice providing unit. The data collection part collects data of pulse, body temperature and the number of steps by using a sensor attached to a collar of the pet. The data transmission unit transmits the data collected by the data collection unit to the server. The data analysis part analyzes the data transmitted by the data transmission part and determines the weight and excretion action of the pet. The emotion estimator reads the emotion of the pet based on the data analyzed by the data analyzer. The advice providing unit provides advice to the owner based on the feeling read by the feeling estimation unit.SELECTED DRAWING: Figure 1