Activity Monitoring and Feedback to Promote an Active Lifestyle and Self Management of Patients with Chronic Disorders
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Abstract
Background
The rapidly changing ratio between number of people with chronic disorders who require care for long periods of time in relation to the number of professional care providers forces us to create innovative approaches for health care service delivery. Remotely Supervised Training (RMT) comprises a potentially effective, individually tailored training anywhere and anytime with an intensity not feasible in an intramural setting.
This paper deals with the experiences gained with such a service: quantitative monitoring of the activity of persons and providing them real-time personalised feedback on their activity level and pattern.
Methods
Patients wear a dedicated activity sensor and a PDA. Activity is monitored using a special purpose sensor, containing 3D accelerometer and a 3D gyroscope. Processing is done on board, converting the accelerometer signals into an activity variable. Via a Bluetooth connection, the data are continuously sent to a PDA. Accumulated activity built up during the day is displayed on the PDA, in comparison to a reference line. Also the actual amount of deviation from this reference is shown to the patient. The reference line can be obtained from a database of values of healthy subjects, but it can also be adjusted by the care provider.
In addition personalised feedback is provided, to increase its convincing power. Beforehand, the patient is asked what kind of activities he likes when he is asked to do more (go for a walk) or less (e.g. reading, have tea).
Results
The first stage, monitoring the activity levels and patterns was carried out in patients with COPD, chronic low back pain, obesitas and chronic fatigue syndrome
If we compare their daily activity patterns, the following observations can be made:
 The activity pattern of healthy subjects is rather constant over the day, declining in the evening.
 The activity pattern of subjects with chronic low back pain show a distinct pattern; with higher activity levels in the morning and declining over the day
 Also the activity patterns of COPD patients show a specific pattern, being rather flat over the day, lower compared to healthy subjects and with a dip around noon
A first clinical study on the effects of feedback was carried out, using a prognostic cohort design. The intervention consisted of a monitoring and a feedback part. During the monitoring part, patients were monitored for four days in their own environment to establish a baseline daily activity pattern. During the feedback part, patients were instructed to use the feedback during two weeks. Fifteen patients with CLBP participated in this study. The mean pain intensity decreased at all day parts during both feedback periods and is the lowest in the second week of feedback.
Conclusions
The paper describes ongoing research. It seems technically feasible to monitor activity level and patters and to provide streaming personalised feedback, which enables patient to change his activity pattern. A first study show the potential of this approach.
The rapidly changing ratio between number of people with chronic disorders who require care for long periods of time in relation to the number of professional care providers forces us to create innovative approaches for health care service delivery. Remotely Supervised Training (RMT) comprises a potentially effective, individually tailored training anywhere and anytime with an intensity not feasible in an intramural setting.
This paper deals with the experiences gained with such a service: quantitative monitoring of the activity of persons and providing them real-time personalised feedback on their activity level and pattern.
Methods
Patients wear a dedicated activity sensor and a PDA. Activity is monitored using a special purpose sensor, containing 3D accelerometer and a 3D gyroscope. Processing is done on board, converting the accelerometer signals into an activity variable. Via a Bluetooth connection, the data are continuously sent to a PDA. Accumulated activity built up during the day is displayed on the PDA, in comparison to a reference line. Also the actual amount of deviation from this reference is shown to the patient. The reference line can be obtained from a database of values of healthy subjects, but it can also be adjusted by the care provider.
In addition personalised feedback is provided, to increase its convincing power. Beforehand, the patient is asked what kind of activities he likes when he is asked to do more (go for a walk) or less (e.g. reading, have tea).
Results
The first stage, monitoring the activity levels and patterns was carried out in patients with COPD, chronic low back pain, obesitas and chronic fatigue syndrome
If we compare their daily activity patterns, the following observations can be made:
 The activity pattern of healthy subjects is rather constant over the day, declining in the evening.
 The activity pattern of subjects with chronic low back pain show a distinct pattern; with higher activity levels in the morning and declining over the day
 Also the activity patterns of COPD patients show a specific pattern, being rather flat over the day, lower compared to healthy subjects and with a dip around noon
A first clinical study on the effects of feedback was carried out, using a prognostic cohort design. The intervention consisted of a monitoring and a feedback part. During the monitoring part, patients were monitored for four days in their own environment to establish a baseline daily activity pattern. During the feedback part, patients were instructed to use the feedback during two weeks. Fifteen patients with CLBP participated in this study. The mean pain intensity decreased at all day parts during both feedback periods and is the lowest in the second week of feedback.
Conclusions
The paper describes ongoing research. It seems technically feasible to monitor activity level and patters and to provide streaming personalised feedback, which enables patient to change his activity pattern. A first study show the potential of this approach.
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