RecoFit: using a wearable sensor to find, recognize, and count repetitive exercises

Although numerous devices exist to track and share exercise routines based on running and walking, these devices offer limited functionality for strength-training exercises. We introduce RecoFit, a system for automatically tracking repetitive exercises - such as weight training and calisthenics - via an arm-worn inertial sensor. Our goal is to provide real-time and post-workout feedback, with no user-specific training and no intervention during a workout. Toward this end, we address three challenges: (1) segmenting exercise from intermittent non-exercise periods, (2) recognizing which exercise is being performed, and (3) counting repetitions. We present cross-validation results on our training data and results from a study assessing the final system, totaling 114 participants over 146 sessions. We achieve precision and recall greater than 95% in identifying exercise periods, recognition of 99%, 98%, and 96% on circuits of 4, 7, and 13 exercises respectively, and counting that is accurate to ±1 repetition 93% of the time. These results suggest that our approach enables a new category of fitness tracking devices.

[1]  Kenneth Meijer,et al.  Activity identification using body-mounted sensors—a review of classification techniques , 2009, Physiological measurement.

[2]  Lawrence R. Rabiner,et al.  A pattern recognition approach to voiced-unvoiced-silence classification with applications to speech recognition , 1976 .

[3]  Janet E. Fulton,et al.  Adult Participation in Aerobic and Muscle-Strengthening Physical Activities — United States, 2011 , 2013, MMWR. Morbidity and mortality weekly report.

[4]  Jin-Hyung Kim,et al.  An HMM-Based Threshold Model Approach for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Chris Rissel,et al.  Promoting walking with pedometers in the community: the step-by-step trial. , 2007, American journal of preventive medicine.

[6]  I. Olkin,et al.  Using pedometers to increase physical activity and improve health: a systematic review. , 2007, JAMA.

[7]  I. Janssen,et al.  Systematic review of the health benefits of physical activity and fitness in school-aged children and youth , 2010, The international journal of behavioral nutrition and physical activity.

[8]  Catrine Tudor-Locke,et al.  Health benefits of a pedometer-based physical activity intervention in sedentary workers. , 2004, Preventive medicine.

[9]  Ulf Ekelund,et al.  The ABC of Physical Activity for Health: A consensus statement from the British Association of Sport and Exercise Sciences , 2010, Journal of sports sciences.

[10]  B. Dobkin,et al.  Reliability and Validity of Bilateral Ankle Accelerometer Algorithms for Activity Recognition and Walking Speed After Stroke , 2011, Stroke.

[11]  Alberto Calatroni,et al.  Improving online gesture recognition with template matching methods in accelerometer data , 2012, 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA).

[12]  Mike Y. Chen,et al.  Tracking Free-Weight Exercises , 2007, UbiComp.

[13]  Sethuraman Panchanathan,et al.  Activity gesture spotting using a threshold model based on Adaptive Boosting , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[14]  P. Boersma ACCURATE SHORT-TERM ANALYSIS OF THE FUNDAMENTAL FREQUENCY AND THE HARMONICS-TO-NOISE RATIO OF A SAMPLED SOUND , 1993 .

[15]  Jerson Laks,et al.  Exercise and Mental Health: Many Reasons to Move , 2009, Neuropsychobiology.

[16]  Miguel A. Labrador,et al.  A Survey on Human Activity Recognition using Wearable Sensors , 2013, IEEE Communications Surveys & Tutorials.

[17]  A. Bauman,et al.  Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. , 2007, Circulation.

[18]  Judy Kruger,et al.  Dietary and physical activity behaviors among adults successful at weight loss maintenance , 2006, The international journal of behavioral nutrition and physical activity.

[19]  G Plasqui,et al.  Daily physical activity assessment with accelerometers: new insights and validation studies , 2013, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[20]  R. S. Jadon,et al.  A REVIEW OF VISION BASED HAND GESTURES RECOGNITION , 2009 .

[21]  Allana G LeBlanc,et al.  ReviewSystematic review of the health benefits of physical activity and fitness in school-aged children and youth , 2010 .

[22]  Gerhard Tröster,et al.  Gestures are strings: efficient online gesture spotting and classification using string matching , 2007, BODYNETS.

[23]  A. Steptoe,et al.  Dose-response relationship between physical activity and mental health: the Scottish Health Survey , 2008, British Journal of Sports Medicine.

[24]  David W. McDonald,et al.  Activity sensing in the wild: a field trial of ubifit garden , 2008, CHI.

[25]  Karen A Schutzer,et al.  Barriers and motivations to exercise in older adults. , 2004, Preventive medicine.

[26]  Gernot Bahle,et al.  What Can an Arm Holster Worn Smart Phone Do for Activity Recognition? , 2011, 2011 15th Annual International Symposium on Wearable Computers.

[27]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[28]  P. Tomporowski Effects of acute bouts of exercise on cognition. , 2003, Acta psychologica.

[29]  Jiangwen Deng,et al.  An HMM-based approach for gesture segmentation and recognition , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[30]  Sunny Consolvo,et al.  Using Multi-modal Sensing for Human Activity Modeling in the Real World , 2010, Handbook of Ambient Intelligence and Smart Environments.

[31]  Oliver Amft,et al.  Adaptive Activity Spotting Based on Event Rates , 2010, 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing.

[32]  S. Sathiya Keerthi,et al.  A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs , 2005, J. Mach. Learn. Res..

[33]  Kristof Van Laerhoven,et al.  myHealthAssistant: a phone-based body sensor network that captures the wearer's exercises throughout the day , 2011, BODYNETS.

[34]  Paul Lukowicz,et al.  Gesture spotting with body-worn inertial sensors to detect user activities , 2008, Pattern Recognit..