11 results about "Walking velocity" patented technology

A wearable walking assist and / or exercise device may detect a start of exercise of the user, select LED lamps to be blinked from the plurality of LED lamps included in the lighting module based on an exercise intensity of the wearable device, determine a blinking period of the selected LED lamps based on a walking speed of the user, and blink the selected LED lamps for the determined blinking period.

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

The application provides a robot testing method and testing equipment, which can save testing cost. The testing method comprises the following steps: when the first sensor and the second sensor both sense the robot, the conveyor belt is controlled to start and gradually accelerate, wherein, during the gradual acceleration, when the second sensor and the third sensor both do not sense the robot, the conveyor belt is controlled to accelerate to a standard speed and run in a direction opposite to the walking direction of the robot; within the first set time of the running of the conveyor belt at the standard speed, if the second sensor and the third sensor both do not sense the robot, it is determined that the walking speed test of the robot is qualified, if the second sensor senses the robot, it is determined that the rated walking speed of the robot is slower, and if the third sensor senses the robot, it is determined that the rated walking speed of the robot is faster.

The invention provides a robot testing method and testing equipment thereof, which can save the testing cost. The testing method comprises the steps that under the condition that both the first sensor and the second sensor sense the robot, the conveyor belt is controlled to be started and gradually accelerated, and in the gradual acceleration process, when both the second sensor and the third sensor do not sense the robot, the conveyor belt is controlled to be started and gradually accelerated; the conveying belt is controlled to accelerate to the standard speed to run, and the running direction of the conveying belt is opposite to the walking direction of the robot; within the first set time when the conveyor belt runs at the standard speed, if neither the second sensor nor the third sensor senses the robot, it is judged that the walking speed of the robot is tested to be qualified, and if the second sensor senses the robot, it is judged that the rated walking speed of the robot is low; if the third sensor senses the robot, it is judged that the rated walking speed of the robot is high.

To provide a walking estimation device and a walking estimation program capable of estimating a walking mode of a pedestrian and calculating an index value highly correlated with a walking speed.SOLUTION: The walking estimation device 1 includes the acceleration sensor 80 that detects acceleration when the pedestrian 100 walks, the peak detection unit 13 that detects a peak based on waveform information of the acceleration obtained by the acceleration sensor 80, and the index value calculation unit 16 that calculates an index value indicating a walking mode of the pedestrian 100 based on waveform information in which a value of the acceleration is equal to or less than a predetermined acceleration between peaks obtained by the peak detection unit 13.SELECTED DRAWING: Figure 3

The present application belongs to the technical field of data processing and computer application, and particularly relates to a business leisure space staying time length and walking speed estimation method based on a zero-inflated Gamma model. Sparse positioning data is used to obtain the total activity time length of tourists in a business leisure space set, estimate the sub-space sequence passed by the tourists, estimate the probability distribution of the staying time length of the tourists in each sub-space, and estimate the probability distribution of the walking speed of the pedestrians using a zero-inflated Gamma model. The method uses relatively easily obtained sparse positioning data, and the staying time length result can be used as an evaluation index of the attraction of the business leisure space, and the walking speed result can be used as a basis for the design and construction of the walking environment, thereby supporting business leisure space planning, design, operation, management and the like. The method is suitable for business street blocks, comprehensive shopping malls, parks, amusement parks, scenic spots and the like, and can be used as a module or algorithm in space utilization monitoring and evaluation work, and is feasible.

The walking speed scale receiving section (111) receives a walking speed scale input as a scale indicating the walking speed of a user. The walking time acquiring section (120) acquires walking time information indicating the length of time of walking by the user as a walking time. The thermal sensation estimating section (130) estimates the thermal sensation after walking by the user based on the received walking speed scale and the acquired walking time information as utilization information.

A micromobility electric vehicle with a controller that operates the vehicle in a walk-assist mode, expanding the population of users that can comfortably use the vehicle. In walk-assist mode, the speed of the vehicle may be limited to a walking speed, regardless of the position of a throttle. In contrast, in a riding mode, the maximum speed may be higher. The walk-assist mode may be entered or exited based on output of one or more sensors, indicating that the user is or is not riding the vehicle or that a user is or is not pushing the vehicle. Such sensors may be positioned in a seat, in a floorboard or on the handlebars of the vehicle. Alternatively or additionally, the sensor may be associated with a control, such as a tab configured to be pressed by a user's thumb when the user is pushing the vehicle.

The method comprises the following steps: firstly, acquiring a continuous walking video stream of a target object in a preset assessment site, and preprocessing the video stream to accurately extract motion data of the target object; secondly, deeply analyzing the motion data by using a gait recognition algorithm to obtain core gait features including a step length sequence and a gait cycle sequence; accurately calculating the target walking speed of the target object based on the step length sequence and the gait cycle sequence, and generating an evaluation result reflecting the walking ability of the target object according to the target walking speed; and finally, the evaluation result is applied to health condition evaluation and fall risk prediction of the target object. According to the invention, no equipment needs to be worn, and non-contact monitoring can be completed only by a common camera, so that the use threshold is reduced, the discomfort caused by wearing the equipment is avoided, and the convenience and accessibility of daily health monitoring are remarkably improved.

The invention belongs to the technical field of data processing and computer application, and particularly relates to a commercial leisure space staying duration and walking speed estimation method based on a zero-expansion Gamma model. The method comprises the following steps: acquiring the total activity duration of tourists in a commercial leisure space set by using sparse positioning data, estimating a subspace sequence through which the tourists pass, and estimating the probability distribution of the residence duration of the tourists in each subspace and the probability distribution of the walking speed of the pedestrians by using a zero-expansion Gamma model. According to the method, sparse positioning data which are relatively easy to obtain are utilized, a stay duration result can be used as an evaluation index of the attraction of the commercial leisure space, a walking speed result can be used as a basis for design and construction of a walking environment, and works such as planning, design, operation and management of the commercial leisure space are supported. The method is suitable for commercial leisure spaces such as commercial street areas, comprehensive shopping malls, parks, amusement parks and scenic spots, can be used as a module or algorithm in space utilization monitoring and evaluation work, and is good in feasibility.

The present disclosure relates to systems and methods adapted to improve gait tracking of individuals with atypical or abnormal walking modes by fusing co-located activity monitoring devices. As described herein, hospital staffs and patients may be equipped with activity monitoring devices that are used by systems and methods to detect proximity of such devices and then update parameters for tracking the gait of the patient. For example, upon detecting that two or more devices are within a near proximity (e.g., a nurse walking with a patient), the estimates of the two devices may be compared. The estimates of both may then be updated by adjusting model parameters, e.g., by assigning a mass weight to both estimates, thereby adjusting to achieve an average velocity, or by a weighted adjustment based on a reliability parameter that indicates the reliability of the individual estimates.