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Intelligent gloves, method and system for calorie consumption and hand posture recognition

A technology of calorie consumption and hand posture, applied in gloves, clothing, sports accessories, etc., can solve the problem that the measurement module is not movable, cannot be truly wearable, and the module cannot be widely used.

Active Publication Date: 2015-09-09
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to realize the preparation detection and calorie consumption during fitness, people have proposed the method of using treadmills, bicycles, and running shoes to detect calorie consumption. However, the detection systems built by these methods have various shortcomings. Calorie consumption is detected by specific sports calculation modules. When using these specific calculation modules for calorie calculation, the measurement module is not mobile and cannot be truly wearable. In current research and industry In production, there is no device that can achieve the above functions, and the existing methods of the latter cannot be widely applied to this scenario due to the particularity of the module

Method used

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  • Intelligent gloves, method and system for calorie consumption and hand posture recognition
  • Intelligent gloves, method and system for calorie consumption and hand posture recognition
  • Intelligent gloves, method and system for calorie consumption and hand posture recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Such as figure 1 As shown, this example provides a smart glove for calorie consumption and hand gesture recognition, including: a processor module, a storage module, a communication module, a perception module, an early warning module, a display module, a power module, a switch module and a cloud server, The storage module, the communication module, the perception module, the warning prompt module, the display module, the power supply module, the switch module and the cloud server are respectively connected to the processor module, wherein the perception module includes a pressure sensor and an IMU inertial unit, and the The pressure sensor and the IMU inertial unit are respectively responsible for sensing the amount of pressure on the hand of the user during the fitness process and the IMU data, and then collect source data for the user's strength training, and transmit the source data to the processor module; the processing The processor module is responsible for prep...

Embodiment 2

[0057] Such as figure 2 and image 3 As shown, this example also provides a method for calorie consumption and hand gesture recognition, using the smart glove described in Embodiment 1, and including the following steps:

[0058] Step S1, using the thin-film pressure sensor of the pressure sensor and the IMU inertial unit to collect source data during strength training;

[0059] Step S2, transmitting the source data to the processor module for processing;

[0060] In step S3, the data obtained by the received pressure sensor and IMU inertial unit is subjected to an ETL process for ETL analysis. The ETL process is to extract, transpose, load and deliver the data obtained in step S2 through ETL technology process;

[0061] And, step S4, calculate the calories consumed, establish a classification model through the support vector machine, use the source data exceeding the strength training as the target action class, and others as the non-target action class; then judge whethe...

Embodiment 3

[0083] Such as Figure 4 As shown, this example also provides a system for calorie consumption and hand gesture recognition, which adopts the method for calorie consumption and hand gesture recognition described in Embodiment 2, and includes the following modules:

[0084] The signal acquisition and calculation module 41 is used to collect the signal when the smart glove is in motion, and evaluate the motion state information for preliminary calculation;

[0085] Anomaly detection module 42, used to identify whether the signal changes abnormally through an anomaly detection algorithm;

[0086] Action judging module 43, a type of support vector machine for distinguishing the target action class from other action classes, taking the abnormal pattern caused by exceeding the strength training threshold as the target action class, and judging whether the movement posture of the smart glove has a posture deviation ;

[0087] And, the alarm module 44 is used for sending out a warni...

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PUM

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Abstract

The invention provides a pair of intelligent gloves, method and system for calorie consumption and hand posture recognition. The pair of intelligent gloves comprises a processor module, a memory module, a communication module, an induction module, an early warning prompt module, a display module, a power module, a switch module and a cloud server. The memory module, the communication module, the induction module, the early warning prompt module, the display module, the power module, the switch module and the cloud server are respectively connected with the processor module. The induction module comprises a pressure sensor and an IMU. The pressure sensor and the IMU are respectively used for being responsible for sensing hand stress strength and IMU data in users' fitness process, collecting source data according to user strength training and sending the source data to the processor module. The processor module is responsible for preprocessing of the source data. According to the pair of intelligent gloves, in the strength training process, the detection accuracy rate of detected motions is high, the rate of false alarm is low, and alarm signals can be sent when the hand posture is deviated.

Description

technical field [0001] The present invention relates to an intelligent detection device, in particular to a smart glove used for measuring calorie consumption and hand posture recognition of strength training, and to a method and system for using the smart glove to recognize calorie consumption and hand posture . Background technique [0002] Nowadays, as the concept of healthy living becomes more and more popular, more and more fitness enthusiasts hope to be able to measure calorie consumption during strength training and subsequent diet adjustments. Energy consumption is not only a cumbersome procedure, but also requires additional equipment, so we urgently need to find a method that can conveniently and effectively detect calorie consumption and action recognition during strength training. [0003] In the daily fitness process, especially strength training, the human body will consume a lot of calories. In order to help the nutritional supplement and diet after training,...

Claims

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Application Information

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IPC IPC(8): A63B71/06A41D19/00
Inventor 邹永攀伍楷舜王建
Owner SHENZHEN UNIV
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