Background: In stroke rehabilitation not only are the levels of physical activity important, but body postures and movements performed during one’s daily-life are also important. This information is provided by a new one-sensor accelerometer that is commercially available, low-cost, and user-friendly. The present study examines the accuracy of this activity monitor (Activ8) in detecting several classes of body postures and movements in people after a stroke. Methods: Twenty-five people after a stroke participated in an activity protocol with either basic activities or daily-life activities performed in a laboratory and/or at home. Participants wore an Activ8 on their less-affected thigh. The primary outcome was the difference in registered time for the merged class “upright position” (standing/walking/running) between the Activ8 and the video recording (the reference method). Secondary analyses focused on classes other than “upright position”. Results: The Activ8 underestimated the merged class “upright position” by 3.8% (775 s). The secondary analyses showed an overestimation of “lying/sitting” (4.5% (569 s)) and of “cycling” (6.5% (206 s)). The differences were lowest for basic activities in the laboratory and highest for daily-life activities at home. Conclusions: The Activ8 is sufficiently accurate in detecting different classes of body postures and movements of people after a stroke during basic activities and daily-life activities in a laboratory and/or at home.

This study assessed whether self-propelled wheelchair driving can be validly detected by a new method using a set of two commonly used accelerometers.In a rehabilitation centre, 10 wheelchair-bound persons with spinal cord injury (SCI) (aged 29-63 years) performed a series of representative daily activities according to a protocol including self-propelled wheelchair driving and other activities. Two ActiGraph GT3X+ accelerometers were used; one was attached at the wrist, the other to the spokes of the wheelchair wheel. Based on the movement intensity of the two accelerometers, a custom-made algorithm in MatLab differentiated between self-propelled wheelchair driving and other activities (e.g. being pushed or arm movements not related to wheelchair driving). Video recordings were used for reference. Validity scores between the accelerometer output and the video analyses were expressed in terms of agreement, sensitivity and specificity scores.Overall agreement for the detection of self-propelled wheelchair driving was 85%; sensitivity was 88% and specificity 83%. Disagreement between accelerometer output and video analysis was largest for wheelchair driving at very low speed on a treadmill, wheelchair driving on a slope on a treadmill, and being pushed in the wheelchair whilst making excessive arm movements.Valid detection of self-propelled wheelchair driving is provided by two accelerometers and a simple algorithm. Disagreement with the video analysis was largest during three atypical daily activities.

Introduction: To set up and guide interventions with the aim to increase physical activity and lower sedentary behavior valid monitoring of physical behavior is essential. The aim of this study was to evaluate the validity of the single-unit Activ8 activity monitor to classify several body postures and movements. Methods: Twelve healthy adults performed a series of activities, representative for everyday life, according to a standard protocol. Activ8 was both worn in the trouser pocket (prescribed location) and fixated to the front of the thigh. Activities were video recorded and analyzed thereafter. Postures and movements that were analyzed were lying/sitting, standing, walking, cycling, and running. Results: The agreement between Activ8 output and video analysis was 89.7% (inter-subject range: 66.0 to 96.6%) for the pocket location and 91.9% (range 85.5 to 95.1%) for the thigh location. Sensitivity and positive predictive value scores for both locations were all above 80%, except for standing (69% or higher). Differences in classified duration of separate postures and movements were within 20% for walking, sitting and running. Conclusion: The Activ8 is a valid instrument to quantify a defined set of body postures and movements. Because of the smaller time difference, the thigh location is preferred for research purposes.

This study investigated hip abductor function by isokinetic dynamometry and gait analysis in adults treated for Perthes disease and its relationship with clinical results. Eighteen patients were divided into two groups on the basis of good versus poor clinical results (IOWA hip-rating scale above or below 90 points). We found that patients with poor clinical results had a lower peak abduction moment (P=0.01) when tested on a dynamometer, and a higher hip abductor moment during gait, as percentage of peak abduction, at the affected hip than at the unaffected hip (P=0.047). Inefficient hip abductor function at the affected hip seems to be associated with poor clinical results.

To compare walking test results with walking in daily life, and to investigate the relationships between walking tests, walking activity in daily life, and perceived mobility problems in patients with post-poliomyelitis syndrome. Twenty-four ambulant patients with post-poliomyelitis syndrome. Walking tests were performed at self-preferred and maximal speed. Walking activity was measured with an ambulatory activity monitor. Heart rate, step cadence and walking speed in the test and in daily life were compared. Walking speed in daily life was represented by the intensity of walking. Perceived mobility problems were assessed with the Nottingham Health Profile. Heart rate during walking was lower in the test at self-preferred speed than in daily life (mean difference: 11.3+/-10.4; p=0.001). Self-preferred walking speed in the test and in daily life correlated significantly (r=0.55; p=0.04). In a sub-group with a test performance below the median value, test performance correlated significantly with walking activity. No significant correlation was found between perceived mobility problems and walking activity. Walking in daily life may be more demanding than walking under standardized conditions. Patients with post-poliomyelitis syndrome with the lowest test performance walked less in daily life. Patients do not necessarily match their activity pattern to their perceived mobility problems.