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Recently, there are many reports on the measurement of mental health conditions as derived from physiological parameters – see references in [1]. Usually, heart-rate or heart rate variability (HRV) has been used for monitoring mental health because of its strong dependency on the autonomic nervous system (ANS) [1-2]. Reference [1] reported that ECG,(More)
A combined method to reduce motion artifact (MA) and power line interference (PLI) for wearable healthcare system is introduced. The proposed method has a block for the reduction of MA using measured electrode-skin impedance as a reference signal and a block for the cancellation of PLI using mixed-signal feedback to relax the dynamic range requirements of(More)
Recently, a wearable body-sensor network realized continuous sleep monitoring by ExG (EEG, EMG, EOG, and ECG) extraction from a sleeper’s face [1]. At least 14 sensors were placed on the face, and were managed by a network controller for sleep monitoring. However, the system in [2] was too bulky and heavy (127×63.5×28mm, 210g) to wear during sleep, and(More)
The wearable mental-health monitoring platform is proposed for mobile mental healthcare system. The platform is headband type of 50 g and consumes 1.1 mW. For the mental health monitoring two specific functions (independent component analysis (ICA) and nonlinear chaotic analysis (NCA)) are implemented into CMOS integrated circuits. ICA extracts heart rate(More)
Online learning, now a popular method of education at the tertiary level, creates new challenges for students and educators. Faculty members may know little about how to assist students in succeeding in this new learning environment, and students may be ill prepared to tackle the new demands put upon them. This research sought to identify dimensions of(More)