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This paper describes a method of detecting an elderly person's chewing motion using a glasses mounted accelerometer. A real-life dataset was collected from 13 elderly adults, aged 65 or older, during meal times in a care facility. A supervised classifier is used to automatically distinguish between epochs of chewing and non-chewing activity. Results are compared to a lab dataset of 5 young to middle-aged adults captured in previous work. K-Nearest Neighbor, Random Forest and Support Vector Machine classifiers are evaluated. All are able to achieve similar performance, with the Support Vector Machine performing the best with an F1-score of 0.73.

It has been shown that gait speed and transfer times are good measures of functional ability in elderly. However, data currently acquired by systems that measure either gait speed or transfer times in the homes of elderly people require manual reviewing by healthcare workers. This reviewing process is time-consuming. To alleviate this burden, this paper proposes the use of statistical process control methods to automatically detect both positive and negative changes in transfer times. Three SPC techniques: tabular CUSUM, standardized CUSUM and EWMA, known for their ability to detect small shifts in the data, are evaluated on simulated transfer times. This analysis shows that EWMA is the best-suited method with a detection accuracy of 82% and an average detection time of 9.64 days.

Although a lot of research effort has focused on the development of new technologies that support healthcare professionals, only a small fraction of these developments penetrate the healthcare market. The reasons for this are multi-factorial, but in our opinion a major problem is the lack of cooperation between engineers and care providers during the early research phase. An improved collaboration between engineers and care providers would ensure that the developed products better match the needs of the care providers and hence facilitate the marketing of the developed product. To improve this collaboration throughout the entire research phase, a new strategy is presented in this paper. An important step in this strategy is the incorporation of an engineering lab within a nursing facility, which is set-up during the project ‘Ingenieurs@WZC’.