Expertise

Isaac is experienced with prototype development, namely sensing physiological signals via electronic sensors and analog conditioning circuit. Isaac has a vast experience in working with signals such as electrocardiogram and ballistocardiogram. As such, he also has in-depth knowledge of physiological signal processing using machine learning techniques. He has applied classification and inference techniques in predicting one's physiological state. Coming from a biomedical engineering background, Isaac has worked with clinicians and heart failure patients in developing unobtrusive zero-effort technological solutions for home monitoring of patients.

Biography

Isaac Chang holds a BASc (Honours) in Biomedical Engineering from Simon Fraser University. His undergraduate projects include a patient tracking system using a ZigBee wireless network, finite element analysis on degenerated lower lumbar spines, and the construction of a rickshaw for measuring walking velocity.

Isaac began his Master of Applied Science in 2010. His research focuses on the development of a smart floor tile that can measure vital signs of an elderly person in a unobtrusive and non-invasive manner. The smart floor tile collects physiological signals such as ballistocardiogram (BCG) and electrocardiogram (ECG) at the sole of one’s foot through electronic using sensors embedded in the tile, including load cells and electrodes.

Publications

Chang, ISJ. Boger, J. Qiu, J. Mihailidis, A. Pervasive Computing and Ambient Physiological Monitoring Devices. In: B. Bouchard, A. Bouzouane, S. Guillet (Eds). Assistive Technologies in Smart Environments for People with Disabilities. Boca Raton, FL: CRC Press; 2015.

Hummel, R. Bradley, TD. Fernie, RG. Chang, ISJ. Alshaer, H. Estimation of Total Sleep Time Using a Novel Head Actigraphy Technique. 2015 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2015), August 25-29, 2015, Milan, Italy.