In recent years, because the wearable medical devices can indicate the health monitoring index of blood sugar, blood pressure, heart rate, oxygen content, temperature, respiration of the human body anytime and anywhere, can also be used for the treatment of various diseases, accompanied by the development of large data, which will bring a subversive revolution for the medical device industry. This paper introduces the development of wearable devices, key technical index of main products, and to make a preliminary study on its quantity control.
Blood Glucose ; Blood Pressure ; Blood Pressure Determination ; Heart Rate ; Humans ; Monitoring, Physiologic ; instrumentation

In recent years, because the wearable medical devices can indicate the health monitoring index of blood sugar, blood pressure, heart rate, oxygen content, temperature, respiration of the human body anytime and anywhere, can also be used for the treatment of various diseases, accompanied by the development of large data, which wil bring a subversive revolution for the medical device industry. This paper introduces the development of wearable devices, key technical index of main products, and to make a preliminary study on its quantity control.

Objective:In this study, a gait acquisition and analysis system is developed to provide a cheap, easy-to-use solution for quantitative recording and analysis of patients' gaits.Methods:From April 2017 to October 2018, we collected the gait data of 19 patients with knee osteoarthritis and 19 healthy volunteers in the orthopaedic outpatient department. Among 19 patients, there were 9 males and 10 females, aged 50.1±9.4 years old. Among 19 healthy volunteers, there were 8 males and 11 females, aged 50.7±10.3 years old. Then, from the collected gait data, the static gait features such as gait speed, step length, stride, and dynamic gait features were automatically calculated, and the statistical difference analysis was finished to determine the correlation between these quantitative gait features and knee osteoarthritis.Results:Firstly, the gait data collected by the depth camera was compared with the data from the multi infrared camera-based motion analysis system (gold standard). The average angle error of the collected knee joint angle was 0.98 degrees, which proved the correctness of the gait data recorded by the depth camera. The statistical difference analysis of gait characteristics between the patient group and the healthy group showed that the gait characteristics with P<0.05 included: gait speed ( r=-0.922, P<0.001), step length ( r=-0.897, P=0.004), stride ( r=-0.914 , P<0.001), dynamic characteristics of angle of knee joint ( r=0.775, P=0.001). Conclusion:The gait acquisition and analysis system based on the depth camera can accurately record and store the gait data of the patients with knee osteoarthritis. Moreover, the extracted quantitative gait features have statistical differences between the patients and the healthy group, which is helpful for the gait analysis of bone joint.