Posture and movement classification: the comparison of tri-axial accelerometer numbers and anatomical placement.

Patient compliance is important when assessing movement, particularly in a free-living environment when patients are asked to don their own accelerometers. Reducing the number of accelerometers could increase patient compliance. The aims of this study were (1) to determine and compare the validity of different accelerometer combinations and placements for a previously developed posture and dynamic movement identification algorithm. Custom-built activity monitors, each containing one tri-axial accelerometer, were placed on the ankles, right thigh, and waist of 12 healthy adults. Subjects performed a protocol in the laboratory including static orientations of standing, sitting, and lying down, and dynamic movements of walking, jogging, transitions between postures, and fidgeting to simulate free-living activity. When only one accelerometer was used, the thigh was found to be the optimal placement to identify both movement and static postures, with a misclassification error of 10%, and demonstrated the greatest accuracy for walking/fidgeting and jogging classification with sensitivities and positive predictive value (PPVs) greater than 93%. When two accelerometers were used, the waist-thigh accelerometers identified movement and static postures with greater accuracy than the thigh-ankle accelerometers (with a misclassification error of 11% compared to 17%). However, the thigh-ankle accelerometers demonstrated the greatest accuracy for walking/ fidgeting and jogging classification with sensitivities and PPVs greater than 93%. Movement can be accurately classified in healthy adults using tri-axial accelerometers placed on one or two of the following sites: waist, thigh, or ankle. Posture and transitions require an accelerometer placed on the waist and an accelerometer placed on the thigh.

[1]  M. Granat,et al.  The validation of a novel activity monitor in the measurement of posture and motion during everyday activities , 2006, British Journal of Sports Medicine.

[2]  Wiebren Zijlstra,et al.  Detection of gait and postures using a miniaturised triaxial accelerometer-based system: accuracy in community-dwelling older adults. , 2010, Age and ageing.

[3]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

[4]  Emma Fortune,et al.  Validity of using tri-axial accelerometers to measure human movement - Part I: Posture and movement detection. , 2014, Medical engineering & physics.

[5]  Compliance with wearing physical activity accelerometers in high school students. , 2009 .

[6]  Martyn Hammersley,et al.  Some Notes on the Terms ‘Validity’ and ‘Reliability’ , 1987 .

[7]  Friedrich Foerster,et al.  Detection of posture and motion by accelerometry : a validation study in ambulatory monitoring , 1999 .

[8]  J. B. J. Bussmann,et al.  Measuring daily behavior using ambulatory accelerometry: The Activity Monitor , 2001, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[9]  Yeh-Liang Hsu,et al.  A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring , 2010, Sensors.

[10]  M. Mathie,et al.  Detection of daily physical activities using a triaxial accelerometer , 2003, Medical and Biological Engineering and Computing.

[11]  C. Matthews,et al.  Best practices for using physical activity monitors in population-based research. , 2012, Medicine and science in sports and exercise.

[12]  Kamiar Aminian,et al.  Ambulatory Monitoring of Physical Activities in Patients With Parkinson's Disease , 2007, IEEE Transactions on Biomedical Engineering.

[13]  David Howard,et al.  A Comparison of Feature Extraction Methods for the Classification of Dynamic Activities From Accelerometer Data , 2009, IEEE Transactions on Biomedical Engineering.

[14]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[15]  L. Mâsse,et al.  Physical activity in the United States measured by accelerometer. , 2008, Medicine and science in sports and exercise.

[16]  D. Nemet,et al.  Health-related knowledge and preferences in low socio-economic kindergarteners , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[17]  Kent Larson,et al.  Real-Time Recognition of Physical Activities and Their Intensities Using Wireless Accelerometers and a Heart Rate Monitor , 2007, 2007 11th IEEE International Symposium on Wearable Computers.

[18]  Matjaz Gams,et al.  Accelerometer Placement for Posture Recognition and Fall Detection , 2011, 2011 Seventh International Conference on Intelligent Environments.

[19]  Melody Oliver,et al.  Utility of accelerometer thresholds for classifying sitting in office workers. , 2010, Preventive medicine.

[20]  Kate Ridley,et al.  Agreement between activPAL and ActiGraph for assessing children's sedentary time , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[21]  J. D. Janssen,et al.  A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity , 1997, IEEE Transactions on Biomedical Engineering.

[22]  Kamiar Aminian,et al.  Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly , 2003, IEEE Transactions on Biomedical Engineering.

[23]  Scott B Going,et al.  Physical activity levels in patients with early knee osteoarthritis measured by accelerometry. , 2008, Arthritis and rheumatism.

[24]  Guang-Zhong Yang,et al.  Sensor Positioning for Activity Recognition Using Wearable Accelerometers , 2011, IEEE Transactions on Biomedical Circuits and Systems.

[25]  K. Aminian,et al.  Physical activity monitoring based on accelerometry: validation and comparison with video observation , 1999, Medical & Biological Engineering & Computing.

[26]  G. ÓLaighin,et al.  Direct measurement of human movement by accelerometry. , 2008, Medical engineering & physics.

[27]  Eliathamby Ambikairajah,et al.  Classification of a known sequence of motions and postures from accelerometry data using adapted Gaussian mixture models. , 2006, Physiological measurement.

[28]  G M Lyons,et al.  Comparison of the performance of the activPAL Professional physical activity logger to a discrete accelerometer-based activity monitor. , 2007, Medical engineering & physics.

[29]  Gye Rae Tack,et al.  Real-time elderly activity monitoring system based on a tri-axial accelerometer , 2010, Disability and rehabilitation. Assistive technology.

[30]  M Honl,et al.  Duration and frequency of every day activities in total hip patients. , 2001, Journal of biomechanics.

[31]  N. Wareham,et al.  Use of accelerometers in a large field-based study of children: protocols, design issues, and effects on precision. , 2008, Journal of physical activity & health.

[32]  P H Veltink,et al.  Detection of static and dynamic activities using uniaxial accelerometers. , 1996, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[33]  Joan Cabestany,et al.  SVM-based posture identification with a single waist-located triaxial accelerometer , 2013, Expert Syst. Appl..

[34]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[35]  L. Klingbeil,et al.  Detecting walking activity in cardiac rehabilitation by using accelerometer , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[36]  D. Altman,et al.  Measuring agreement in method comparison studies , 1999, Statistical methods in medical research.

[37]  G M Lyons,et al.  A description of an accelerometer-based mobility monitoring technique. , 2005, Medical engineering & physics.

[38]  M. Hagströmer,et al.  Physical activity and inactivity in an adult population assessed by accelerometry. , 2007, Medicine and science in sports and exercise.