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As part of a sleep monitoring project, we used actigraphy based on body-worn accelerometer sensors to remotely monitor and study the sleep-wake cycle of elderly staying at nursing homes. We have conducted a fifteen patient trial of a sleep activity pattern monitoring (SAPM) system at a local nursing home. The data was collected and stored in our server and the processing of the data was done offline after sleep diaries used for validation and ground truth were updated into the system. The processing algorithm matches and annotates the sensor data with manual sleep diary information and is processed asynchronously on the grid/cloud back end. In this paper we outline the mapping of the system for grid / cloud processing, and initial results that show expected near-linear performance for scaling the number of users.

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