Smart Homes for Elderly Healthcare-Recent Advances and Research Challenges.

Advancements in medical science and technology, medicine and public health coupled with increased consciousness about nutrition and environmental and personal hygiene have paved the way for the dramatic increase in life expectancy globally in the past several decades. However, increased life expectancy has given rise to an increasing aging population, thus jeopardizing the socio-economic structure of many countries in terms of costs associated with elderly healthcare and wellbeing. In order to cope with the growing need for elderly healthcare services, it is essential to develop affordable, unobtrusive and easy-to-use healthcare solutions. Smart homes, which incorporate environmental and wearable medical sensors, actuators, and modern communication and information technologies, can enable continuous and remote monitoring of elderly health and wellbeing at a low cost. Smart homes may allow the elderly to stay in their comfortable home environments instead of expensive and limited healthcare facilities. Healthcare personnel can also keep track of the overall health condition of the elderly in real-time and provide feedback and support from distant facilities. In this paper, we have presented a comprehensive review on the state-of-the-art research and development in smart home based remote healthcare technologies.

Technique to estimate human reaction time based on visual perception.

The design and implementation of a wearable system to estimate the human reaction time (HRT) to visual stimulus based on two identical wireless motion sensors are described. Each sensor incorporates a motion sensor (gyroscope), a processor and a transceiver operating at the industrial, scientific and medical frequency of 2.45 GHz. Relevant tests to estimate the HRT are performed in two different scenarios including simple and recognition tests for 90 pairs of measurements. The obtained results are compared with a computer-based system to determine the accuracy of the proposed system. The root mean square error, standard deviation error and mean error of the results are 2.88, 6.17 and 0.3 ms for simple test while for recognition test as low as 3.34, 7.83 and 0.35 ms, respectively. The outcomes of the HRT estimation tests confirm HRT can increase by 40-87% due to increased fatigue levels.