65 citations · 93 across the 21 of their papers we have counts for
5 papers · 1 filter
Neural Contextual Bandits Based Dynamic Sensor Selection for Low-Power Body-Area Networks
Berken Utku Demirel, Luke Chen, Mohammad Abdullah Al Faruque
Providing health monitoring devices with machine intelligence is important for enabling automatic mobile healthcare applications. However, this brings additional challenges due to…
SELF-CARE: Selective Fusion with Context-Aware Low-Power Edge Computing for Stress Detection
Nafiul Rashid, Trier Mortlock, Mohammad Abdullah Al Faruque
Detecting human stress levels and emotional states with physiological body-worn sensors is a complex task, but one with many health-related benefits. Robustness to sensor measureme…
Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor
Nafiul Rashid, Luke Chen, Manik Dautta +3
Stress is a physiological state that hampers mental health and has serious consequences to physical health. Moreover, the COVID-19 pandemic has increased stress levels among people…
Energy-efficient Blood Pressure Monitoring based on Single-site Photoplethysmogram on Wearable Devices
Wenrui Lin, Berken Utku Demirel, Mohammad Abdullah Al Faruque +1
The paper proposes accurate Blood Pressure Monitoring (BPM) based on a single-site Photoplethysmographic (PPG) sensor and provides an energy-efficient solution on edge cuffless wea…
Single-Channel EEG Based Arousal Level Estimation Using Multitaper Spectrum Estimation at Low-Power Wearable Devices
Berken Utku Demirel, Ivan Skelin, Haoxin Zhang +2
This paper proposes a novel lightweight method using the multitaper power spectrum to estimate arousal levels at wearable devices. We show that the spectral slope (1/f) of the elec…