Wearable digital self-tracking technology has become more accessible to the public in recent years with the development of connected portable devices (such as smart phones, smart watches, smart bands, and other personal biological monitoring devices), human biosensors, as well as information management systems designed for monitoring, storing and analyzing human self-tracking data. The proliferation of such technology has made it much easier than any time before to collect biological and physiological signals, such as the electrocardiogram (ECG), oxygen saturation (SpQ2), heart rate (HR), the electroencephalogram (EEG), Galvanic Skin Response (GSR), blood pressure/oxygen level, body temperature, etc. These self-tracking data can help us better understand each individual’s health conditions by monitoring and analyzing such data.  As a result, mining wearable data has been gaining significant attention from both industry and academia in recent years.

This workshop focuses on technologies for generating, archiving, and analyzing self-monitored data for health-related applications. The objectives of the workshop include (1) to bring together researchers and practitioners from both industry and academia who are actively working in wearable technology for healthcare to present their latest research, (2) to attract healthcare sensor developers and healthcare service providers to discuss the challenges and opportunities in developing and adopting cutting-edge healthcare wearable products or services, (3) to create a community of researchers and practitioners who worked in the areas of hardware sensors, wearable/healthcare related industry, and data mining/machine learning, that will enable the innovation for next generation healthcare solution, and (4) to have a platform for researchers and practitioners to report/demonstrate/discuss recent innovations and developments.