Identifying irregular activity sequences: an application to passive household monitoring
针对被动传感器（如红外运动传感器）采集的日常触发事件序列，提出一种检测细微变化的方法，同时考虑日常波动和每日事件数量差异，有助于监测老年人健康状况。
Abstract Approximately one in five people will live to see their 100th birthday due to advancements in modern medicine and other factors. Over 65’s constitute 42% of elective admissions and 43% of emergency admissions to hospitals. Increasingly, people are turning to technology to help improve health and care of the elderly. There is mixed evidence of the success of wearables in older populations with a key barrier being adoption. In contrast, passive sensors such as infra-red motion and plug sensors have had more success. These passive sensors give us a sequence of categorical “trigger” events throughout the day. This paper proposes a method for detecting subtle changes in sequences while taking account of the natural day-to-day variability and differing numbers of “trigger” events per day.