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Brick Computing: Embedded, Autonomous, and Passive Physiological Monitoring

Keywords: Smart home technology, physiological monitoring, noninvasive vital sign measurement, embedded computing


A person’s physiological well-being is central to his or her overall health, and therefore, quality of life. By sampling a person’s physiological status often, a holistic and dynamic representation of his or her health can be constructed. Analyses of these measurements can reveal both positive and negative changes in short and long health, allowing the person being monitored and his or her clinicians to make more informed decisions regarding health management decisions.

There are several physiological measuring devices that have been developed, including a wearable device can measure Electrocardiography (ECG), Electromyography (EMG), Gavanic skin response, respiration rate, oxygen saturation rate, blood pressure, and body temperature [1]. This technology has been adapted to integrate with commercially available devices like cell phone. An example of this application is a cell phone called H’andy sana, which can measure ECG and provides monitoring and networking services for people with cardiovascular diseases [2].

The risk of having one or more morbidities that require physiological monitoring increases with age. Active, portable devices may not be ideal for monitoring older adults because the users may forget to wear the device or could use them incorrectly [3]. This is a greater concern when an individual has reduced cognitive ability, such as a person with dementia. Therefore, although robust products are available, they may be inappropriate for use by older adults. Passive devices that are embedded into the environment and require little or no effort on the part of the user are likely more suitable for monitoring the health of older adults. One approach to counter these problems is to use passive monitoring, where the monitoring device is embedded in the environment and requires little or no effort from the user to function [3]. A number of passive monitoring devices for physiological monitoring have been developed recently, including a toilet, bed, and bathtub [4], where each device is able to autonomously measure physiological parameters at different times of the day.

Overview of Research

While these devices are useful, it would be advantageous to measure several vital signs simultaneously with one device to provide a more integrated view of the subject’s physiological state, as well reduce discrepancies caused by temporal differences of each measurement. Furthermore, the usability of such devices may be improved through technologies that do not require any active engagement by the user to collect the required data, but rather are naturally incorporated into the user’s everyday life and collect data automatically.

We have developed a smart instrumented floor tile that measures two physiological signals, namely ballistocardiogram (BCG) and electrocardiogram (ECG) data from a stationary person standing on the tile. From these signals, we aim to extract vital signs such as heart rate, respiration rate, and systolic blood pressure. In order to develop algorithms needed to extract vital signs are available, we have collected pilot data from 60 healthy adults between 19 and 65 years old of age to evaluate the efficacy of the floor tile.

Research Team

Isaac Chang, University of Toronto

Alex Mihailidis, University of Toronto

Jennifer Boger, University of Waterloo


  1. A. Pantelopoulos and N. Bourbakis. (2008). "A survey on wearable biosensor systems for health monitoring," in Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, pp. 4887.
  2. H'andy sana 210, "H'andy sana 210," Accessed on November 19, 2010.
  3. M. Alwan. (2009). "Passive in-home health and wellness monitoring: overview, value and examples," Conference Proceedings of the IEEE Engineering in Medicine and Biology Society, pp. 4307-4310.
  4. K. Motoi, M. Ogawa, H. Ueno, Y. Kuwae, A. Ikarashi, T. Yuji, Y. Higashi, S. Tanaka, T. Fujimoto, H. Asanoi and K. Yamakoshi. (2009). "A fully automated health-care monitoring at home without attachment of any biological sensors and its clinical evaluation," Conference Proceedings of the IEEE Engineering in Medicine and Biology Society, pp. 4323-4326.