Fit-NES: wearable bracelet for heart rate monitoring

The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices

Validation of a commercial android smartwatch as an activity monitoring platform

Activity monitoring (AM) is an established technique for the assessment of a person's physical activity. With the rapid rise of smartwatch technology, this platform presents an interesting opportunity to use a device for AM that has both the ability to monitor activity and also the ability to interface seamlessly with other healthcare systems. There are questions however around the suitability of smartwatches as monitoring devices. This paper presents a validation of one smartwatch, the ZGPAX S8, for use as an activity monitor. Two experiments are presented: a physical manipulation test and a co-location test. In the physical manipulation test, three S8s are compared to a reference accelerometer under human physical manipulation. In the co-location test, the smartwatch is used alongside a reference device for a period of three hours by four participants to assess both the accelerometer data and the results of processing on data from both devices. Findings from these experiments show that the S8 accelerometer has a good correlation and limits of agreement in the physical manipulation test (r 2 ~ 0.95, CR ~ 2.5 m/s 2 ), and excellent correlation and limits of agreement in the analysis of processed data from the co-location experiment (r 2 ~ 0.99, CR ~ 0.23). From these results, the S8 is evaluated to be a suitable device for AM. Some specific limitations in the S8 are identified such as data range clipping, time drift and sample rate consistency, but these are not found to impact on the suitability of the device once algorithmic processing is applied to the data