CDH presented two papers at Ubicomp/ISWC2021. 

Extremely low-power sensing systems need to minimise their sensor sampling and data processing. Can we do better than state-of-the-art in sub-Nyquist sampling and compressive sensing? Yes, we can! Our new paper Context-Adaptive Sub-Nyquist Sampling for Low-Power Wearable Sensing Systems presents a c... 

IEEE Pervasive Computing (Impact Factor: 4.4) has just release Issue 3 of 2020 with a Special Issue on Personalised Pervasive Health. 

In the paper “Estimating wearable motion sensor performance from personal biomechanical models and sensor data synthesis”, we present a fundamentally novel simulation methodology to estimate the performance of wearable motion sensors using personalised biomechanical models and sensor data synt... 

SI Fabricating Pervasive Computing Systems is out 

In the paper “Synthesising Motion Sensor Data from Biomechanical Simulations to Investigate Motion Sensor Placement and Orientation Variations”, we investigate for the first time effects of sensor positioning and orientation variation using biomechanical simulations and motion data synthesis. ... 

The chair is presenting three research papers at Ubicomp/ISWC 2018 conferences in Singapore. 

For the first time we design eyeglasses temples and 3D print conductive lines and electromyography (EMG) electrodes on the temples according to personal head shapes. We demonstrate that the printed lines and electrodes provide adequate signal quality to acquire the Temporalis muscle activation during chewing. 

We analyse for the first time a unique database of over 2000 runners regarding their 10km performance in relation to anthropometrics, resting heart rate (HR) and heart rate variability (HRV), and training patterns regularly acquired over two years using smartphones. 

A new Frontiers publication: We are investigating whether wearable sensors can help track patients motor relearning progress in particular to regain walking performance. We developed a novel, intuitive marker "Convergence Point (CP)" that indicates the projected point in time at which patients move affected and less affected body sides similarly.