5 accepted papers
Precise microfluidic control is essential for biomedical diagnostics. Compared to traditional PCB-based DMFB, standard CMOS-based digital microfluidic biochips (DMFB) can integrate sensing, heating, and actuation on a single chip, eliminating the need for external equipment [1]. However, CMOS-DMFB a…
Deep neural networks (DNNs) are known to perform well when deployed to test distributions that shares high similarity with the training distribution. Feeding DNNs with new data sequentially that were unseen in the training distribution has two major challenges --- fast adaptation to new tasks and ca…
The adoption of biomedical signals such as photoplethysmogram (PPG) and electrocardiogram (ECG) for health parameter estimation on wearable devices is growing in tandem with the increase of attention in mobile healthcare. In our work, we use PPG signals extracted from PPG sensors which are used for…
Remote heart rate estimation is the measurement of heart rate without any physical contact with the subject and is accomplished using remote photoplethysmography (rPPG) in this work. rPPG signals are usually collected using a video camera with a limitation of being sensitive to multiple contributing…
Deciding the amount of neurons during the design of a deep neural network to maximize performance is not intuitive. In this work, we attempt to search for the neuron (filter) configuration of a fixed network architecture that maximizes accuracy. Using iterative pruning methods as a proxy, we paramet…