Hardware implementation method and combination of emotion perception function of intelligent wearable device

Abstract

Disclosed is a hardware implementation method of an emotion perception function of an intelligent wearable device. The method includes the following steps: a PPG(photoplethysmography) sensor and an accelerometer transmit collected PPG signals and acceleration signals to a FPGA(Field-Programmable Gate Array) chip; the FPGA chip carries out feature extraction of the PPG signals and the accelerationsignals to obtain four physical quantities of heart rate, respiration rate, moving speed and moving frequency; and inputting the four physical quantities of heart rate, respiration rate, moving speedand moving frequency into an RHPNN(Robust Heteroscedastic Probabilistic Neural Network) based on probability to realize classification of emotion. The hardware implementation method and combination sense changes of emotion of a user in real time, remind the user to pay attention to metal health and adjust a working state in time, provide guarantee for mental health of the user, and can improve theworking efficiency of the user.

Description

technical field [0001] The invention relates to the field of smart wearables, in particular to a hardware implementation method and combination of the emotion perception function of smart wearable devices. Background technique [0002] With the development of mobile communication technology and the increasing popularity of the mobile Internet, the traditional Internet has been migrating to the mobile Internet, and smart wearable devices have developed very rapidly in recent years. Smart wearable devices are new forms of terminal devices that can be worn directly on the body or exist in the form of accessories or carry-on items, integrate software and hardware, and have certain computing capabilities. It seems difficult to combine wearable devices and FPGAs. According to market conditions, most of the current wearable devices use ARM architecture processors. It is easier to achieve the optimal solution. And Lattice has pulled the battlefield of wearable chips from the ARM a...

AI Technical Summary

Problems solved by technology

[0004] Artificial neural networks are widely used in the fields of intelligent control and pattern recognition, but there are two main problems in the traditional general-purpose processor-based software implementation method: one is the low degree of parallelism, and the calculation speed cannot meet the real-time requirements of the scene; the other is Many embedded applications have strict restrictions on system stability, chip power and size

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