Activity recognition using low resolution infrared array sensor

Abstract

Now, aging society is a worldwide problem, and the population of people aged over 60 years is growing faster than any other age group. Therefore, monitoring services for elderly people are attracting a great deal of attention. We have proposed a fall detection method using a low resolution infrared array sensor to inform an unexpected falling in our previous work. However, knowing daily fundamental activities of elderly people is also important to prevent future accidents. In this paper, we propose an activity recognition method using a low resolution infrared array sensor. This sensor can detect temperature on a two dimensional area. From the viewpoint of general versatility (available in darkness), cost, size, privacy (low resolution), and availability (commercial off-the-shelf), this sensor is better than other sensing devices like video cameras, Doppler radars, acceleration sensors, and so on. In the proposed method, temperature distribution obtained from the sensor is analyzed and classified into five fundamental states: “No event”, “Stopping”, “Walking”, “Sitting”, and “Falling” (emergency situation). As a result of experiments, our proposed method achieved recognition accuracy of 100 %, 94.8 %, 99.9 %, and 78.6 % respectively. In particular, 100 % accuracy of “Falling” recognition was achieved.