A Survey of Physical Activity Monitoring and Assessment Using Internet of Things Technology
Jun Qi, Po Yang, Dina Fan, Zhikun Deng · 2015
As a key health indictor, daily physical activity (PA) data has great significance on diagnosis and treatment of many chronic diseases. Numerous studies have been carried out for accurately monitoring and assessing physical activity. Most attentions of these studies focus on designing standalone highly accurate wearable sensors or investigating advance machine learning algorithms to train these PA data in a controlled environment. But the wide use of cost-effective wearable devices and mobile apps makes it possible to monitor and access PA into a more open and connective Internet of Things (IoT) environment. Yet, it still lacks of a systemic survey on how to effectively transfer classic PA monitoring and assessment (PAMA) technologies into a heterogeneous device connected IoT environment. In an effect to understand the development of IoT technologies in PAMA, this paper reviews current research of PAMA technologies from an IoT layer-based perspective, and also identifies research challenges and future trends. A main contribution of this review paper is that it is first attempt to categorize classic PAMA technologies into an IoT architecture systematically.