The Development and Testing of an Electronic Tool to Measure Physical Activity in Domestic Settings

Context Sensitive Measurement of Physical Activity

The purpose of this study is to develop a tool that can more accurately assess the intensity and kind of physical activity that a person performs. The experimental tool, which will use a mobile computing device as a way of automatically identifying when a certain activity is being performed and at what intensity, will be tested against a self reported paper diary of activities performed on a day to day basis. It is hoped that this study will increase understanding of the health benefits of certain types of physical activity performed in the home.

Engaging in regular physical activity that requires a moderate to vigorous effort is related to good health and a reduced risk of a multitude of diseases. Currently physical activity and health promotion research is limited by self- report data that is confounded by participants' ability to accurately remember and record their physical activity. A potentially new method of accurately assessing moderate-intensity physical activity is called context sensitive- ecological momentary assessment (CS-EMA). Mobile computing devices (personal computing devices, PDAs) that automatically identify when a specific type of physical activity (e.g., moderate-intensity physical activity) is being performed has the potential to provide valuable objective data for naturalistic, experimental, and clinical intervention research purposes, and has the potential for educational, recreational, and clinical applications. The goal of this exploratory study is to assess the accuracy of two methods of collecting data on moderate-intensity physical activity. The study will compare the use of a paper diary to collect self-reported data on moderate-intensity physical activities performed throughout the day to self-reported data collected using ecological momentary assessment methods which are facilitated by a PDA that cues the participant to record when specific intensity levels of physical activity are achieved. This study will also develop algorithms that will automatically identify specific types of physical activities being performed. The data collected from the heart rate monitor, motion sensor, and information requested directly from the participant via the PDA interface will be used to train pattern recognition systems to classify the intensity and type of physical activity being performed by the participant. This study will contribute to research on context- awareness and human activity recognition.

Inclusion Criteria:

To be eligible, a person will need to be:

• A full-time employee in one of the two BMC hospital departments, or a house cleaner who is not employed by BMC
• At least 18 years of age
• Performing regular duties at the time of their participation (not on reduced duties due to illness, injury, disability, etc.)
• Have a resting HR>50 and <120 bpm
• Not be taking medication that can alter HR at rest or exercise (e.g. beta-blockers)
• Able to understand spoken and written English
• Not excluded from participation by their manager for disciplinary or other reasons.

Exclusion Criteria:

To be excluded, a person will be any of the following:

• Part-time employee of the two BMC hospital departments,or a house cleaner who is not employed by BMC
• Less than 18 years of age
• Unable to perform full regular duties due to illness, injury, disability, etc.
• Have >120 bpm and resting HR<50
• Taking medication that can alter HR at rest or exercise (e.g. beta-blockers)
• Unable to understand spoken and written English
• Excluded from participation by their manager for disciplinary or other reasons.