ABSTRACT
Remote health monitoring is one topic that needs a lot of attention due to the rising number of pandemics. Body fever and low blood oxygen saturation level is clear symptom of COVID-19. Different data display and transmission systems can make monitoring vital indicators such as body temperature, pulse oximeter and heart rate. In this research, thermometry and pulse oximetry have been designed and built with an online monitoring system based on Android. The MAX30205 thermometer sensor was utilized in this study to detect body temperature with high precision. Also, the MAX30102 module was used to detect blood oxygen saturation and heart rate with proper accuracy. The sensors were controlled by an ESP32 microcontroller on the TTGO board, and the measured temperature, blood oxygen saturation level and heart rate were transmitted through Bluetooth to Android devices. These three parameters can be assessed long distances using these circuit and application designs in pandemic conditions. The device's performance was tested successfully and compared with the results of a reference thermometer and finger pulse oximeter. © 2022 IEEE.
ABSTRACT
The physical therapy generally requires direct assistance from therapists continuously, however, the time is very limited. Moreover, the social distancing policy in the COVID-19 pandemic period made the patient could not come to rehabilitation center for physical therapy. Remote physical therapy is suggested to reduce dependency of therapist for conducting the physical therapy. However, there is few information about the necessary parameters in lower limb monitoring of post-stroke patient. Therefore, in this paper, a review for designing a low-cost online homecare physical therapy monitoring system is proposed. Article finding had been done using online search engine Google Scholars to conclude the design of the online monitoring system. Several keywords had been used, such as “online stroke rehabilitation monitoring,” “stroke rehabilitation parameters,” “stroke monitoring Internet of Things,” and “lower limb stroke monitoring.” The results show that the necessary monitor parameters are lower limb kinematics and dynamics, which can be complimented by bio-signal data, such as EMG. The lower limb monitoring system can use IMU, muscle sensor, and footswitches to measure the necessary parameters. IMU measures the lower limb kinematics because it provides wide range of measurement. Muscle sensor, which compatible to microcontroller, measures the EMG. Lastly, the footswitches detect the gait phases, which classify the measured data for more in-depth analysis. The mentioned sensors are cheap and available in the online market of Indonesia, which is suitable to realize a low-cost lower limb monitoring system. The research finding also suggests quick and accurate feedback mechanism for improving the training quality, which the feedback is combination of therapist opinion and artificial intelligence prediction. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.