Detection of physical activities using a physical activity monitor system for wheelchair users.

Availability of physical activity monitors for wheelchair users can potentially assist these individuals to track regular physical activity (PA), which in turn could lead to a healthier and more active lifestyle. Therefore, the aim of this study was to develop and validate algorithms for a physical activity monitoring system (PAMS) to detect wheelchair based activities. The PAMS consists of a gyroscope based wheel rotation monitor (G-WRM) and an accelerometer device (wocket) worn on the upper arm or on the wrist. A total of 45 persons with spinal cord injury took part in the study, which was performed in a structured university-based laboratory environment, a semi-structured environment at the National Veterans Wheelchair Games, and in the participants' home environments. Participants performed at least ten PAs, other than resting, taken from a list of PAs. The classification performance for the best classifiers on the testing dataset for PAMS-Arm (G-WRM and wocket on upper arm) and PAMS-Wrist (G-WRM and wocket on wrist) was 89.26% and 88.47%, respectively. The outcomes of this study indicate that multi-modal information from the PAMS can help detect various types of wheelchair-based activities in structured laboratory, semi-structured organizational, and unstructured home environments.

[1]  Stephen Sprigle,et al.  Validation of an accelerometer-based method to measure the use of manual wheelchairs. , 2012, Medical engineering & physics.

[2]  J. Hardin,et al.  Electronic feedback in a diet- and physical activity-based lifestyle intervention for weight loss: a randomized controlled trial , 2011, The international journal of behavioral nutrition and physical activity.

[3]  H J Stam,et al.  Validity of the detection of wheelchair propulsion as measured with an Activity Monitor in patients with spinal cord injury , 2005, Spinal Cord.

[4]  R. Cooper,et al.  Predicting energy expenditure of manual wheelchair users with spinal cord injury using a multisensor-based activity monitor. , 2012, Archives of physical medicine and rehabilitation.

[5]  B. Fernhall,et al.  Health Implications of Physical Activity in Individuals with Spinal Cord Injury: A Literature Review , 2008, Journal of health and human services administration.

[6]  Bradley N. Hedrick,et al.  Descriptive epidemiology of physical activity in university graduates with locomotor disabilities , 1997, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.

[7]  A. Buchholz,et al.  Energy expenditure in chronic spinal cord injury , 2004, Current opinion in clinical nutrition and metabolic care.

[8]  P. London Injury , 1969, Definitions.

[9]  Marcel Zeelenberg,et al.  Data analysis 2 , 2016 .

[10]  R. Aungst,et al.  Healthy People 2020 , 2013, American Journal of Kidney Diseases.

[11]  R A Cooper,et al.  Physical activity classification utilizing SenseWear activity monitor in manual wheelchair users with spinal cord injury , 2013, Spinal Cord.

[12]  R. Cooper,et al.  Development and evaluation of a gyroscope-based wheel rotation monitor for manual wheelchair users , 2013, The journal of spinal cord medicine.

[13]  B. Belza,et al.  Actigraphy as a Measure of Physical Activity for Wheelchair Users With Spinal Cord Injury , 2004, Nursing research.

[14]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[15]  Stefania Salmaso,et al.  Features and Initial Assessment of the Italian Behavioral Risk Factor Surveillance System (PASSI), 2007-2008 , 2010, Preventing chronic disease.

[16]  M. Boninger,et al.  Assessing mobility characteristics and activity levels of manual wheelchair users. , 2007, Journal of rehabilitation research and development.

[17]  M. Granat,et al.  Development and validation of a physical activity monitor for use on a wheelchair , 2011, Spinal Cord.

[18]  Stephen S. Intille,et al.  Design of a wearable physical activity monitoring system using mobile phones and accelerometers , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  Weimo Zhu,et al.  Estimating MET values using the ratio of HR for persons with paraplegia. , 2010, Medicine and science in sports and exercise.

[20]  J. Rimmer,et al.  Obesity and Overweight Prevalence Among Adolescents With Disabilities , 2011, Preventing chronic disease.