Bed-ridden person detection system and method based on long short-term memory neural network

Abstract

The invention relates to a bedridden person detection system and method based on a long short-term memory neural network. The system comprises a sensor module, a data acquisition module, a data preprocessing module, a feature extraction module and an output module. The sensor module, the data acquisition module, the data preprocessing module, the feature extraction module and the output module are connected in sequence. The system is arranged on a mattress and is used for continuously, quickly and highly accurately detecting the on-bed postures of the old, the disabled and the long-term bedridden patient; by detecting the posture of the bedridden patient, the bedridden patient is efficiently nursed, and the burden of nurses is relieved.

Description

technical field [0001] The invention relates to the technical field of intelligent detection, in particular to a detection system and method for a bedridden person based on a long-short-term memory neural network. Background technique [0002] At present, most developed countries are experiencing a crisis of population aging. China has become the country with the largest elderly population in the world and one of the countries with the fastest aging population. How to effectively fill the gap in the nursing industry has become a top priority. In hospital nursing work, bedridden patients are often accompanied by various complications, such as falling out of bed, pressure bedsores, urinary incontinence and other problems. Therefore, how to efficiently care for bedridden patients and reduce the burden on nursing staff is a new direction for alleviating aging. [0003] Existing monitoring systems for bedridden patients can be divided into pressure sensors for posture recogniti...

AI Technical Summary

Problems solved by technology

Image recognition involves the privacy of the patient, and the posture cannot be detected well after the patient is covered with a quilt

However, wearable devices are not very comfortable for bedridden patients. At the same time, the devices need to be charged regularly, which will cause certain troubles to nursing care.

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