Wearable lower limb rehabilitation exercise gait monitoring analysis device

Abstract

The invention discloses a wearable lower limb rehabilitation exercise gait monitoring analysis device which is used for rehabilitation exercise monitoring guidance for patients performing limb rehabilitation exercise after leaving hospital. The wearable lower limb rehabilitation exercise gait monitoring analysis device comprises a server side, a patient side and a doctor side. The patient side and the doctor side are respectively in communication connection with the server side. The patient side collects patient gait data and vital sign data which are monitored by a hardware device and uploads the data to the server side. The doctor side obtains the patient gait data and the vital sign data from the server side and performs analysis processing on the obtained data. The patient side is composed of a wearing main body and a positioning auxiliary. The positioning auxiliary is connected with the wearing main body through wireless communication. The wearing main body comprises a processor, a motion capture unit, a vital sign monitoring unit, a data connection unit, a battery unit, a memory, a feedback module and an auxiliary supporting module. The wearable lower limb rehabilitation exercise gait monitoring analysis device mainly monitors gait data during short-distance walking; and different from a wearable device for running and recording gait, the wearable lower limb rehabilitation exercise gait monitoring analysis device is more accurate in distance and gait monitoring.

Description

technical field [0001] The invention relates to a gait monitoring device, in particular to a wearable lower limb rehabilitation exercise gait monitoring and analysis device. Background technique [0002] For patients with hemiplegia who are bedridden for a long time, patients with cerebral infarction, or patients who need rehabilitation exercises after lower limb surgery such as lower limb fracture reduction and lower limb joint replacement, rehabilitation exercise is very important, among which walking exercise is particularly important. Rehabilitation exercises often lack guidance, and it is difficult for doctors to come to monitor and guide, and cannot timely know the patient's rehabilitation situation, and cannot make corrections and understanding in time. This has caused many misunderstandings in the rehabilitation exercise of patients, affecting the effect of rehabilitation. The opposite effect. [0003] The wearable step counting devices currently on the market focus...

AI Technical Summary

Problems solved by technology

[0002] For patients with hemiplegia who are bedridden for a long time, patients with cerebral infarction, or patients who need rehabilitation exercises after lower limb surgery such as lower limb fracture reduction and lower limb joint replacement, rehabilitation exercise is very important, among which walking exercise is particularly important. Rehabilitation exercises often lack guidance, and it is difficult for doctors to come to monitor and guide, and cannot timely know the patient's rehabilitation situation, and cannot make corrections and understanding in time. This has caused many misunderstandings in the rehabilitation exercise of patients, affecting the effect of rehabilitation. opposite effect

[0003] The current wearable step counting devices in the market focus on detecting the number of steps and distance when running, but the monitoring is not accurate when walking a short distance

Patients who need rehabilitation exercises after lower limb surgery have short walking distances. Today's step-counting equipment is difficult to meet the requirements, and does not have the function of gait analysis and monitoring. It is more inclined to count and guide healthy people's sports.

The gait analysis equipment used in the hospital is bulky and cannot analyze the patient's gait in real time, so it does not meet the needs of walking on the ground after surgery

Moreover, large-scale equipment and instruments will make patients more restrained, and the exercise data obtained in the unnatural state will deviate from the natural state, which is not conducive to accurately grasping the recovery situation, and the patients will also cause a lot of financial burden to go to and from the hospital.

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