Instantaneous VO2 from a wearable device.

We present a method for calculating instantaneous oxygen uptake (VO2) through the use of a non-invasive and non-obtrusive (i.e. without a face mask) wearable device, together with its clinical evaluation against a standard technique based upon expired gas calorimetry. This method can be integrated with existing wearable devices, we implemented it in the "Device for Reliable Energy Expenditure Monitoring" (DREEM). The DREEM comprises a single lead electrocardiogram (ECG) device combined with a tri-axial accelerometer and is worn around the waist. Our clinical evaluation tests the developed method against a gold standard for VO2, expired gas calorimetry, using an ethically approved protocol comprising active exercise and sedentary periods. The study was performed on 42 participants from a wide sample population including healthy people, athletes and an at-risk health group including persons affected by obesity. We developed an algorithm combining heart rate (HR) and the integral of absolute acceleration (IAA), with results showing a correlation of r = 0.93 for instantaneous VO2, and r = 0.97 for 3 min mean VO2, this is a considerably improved estimation of VO2 in comparison to methods utilising HR and IAA independently.

[1]  L. Godderis,et al.  Determinants of maximal oxygen uptake (VO2 max) in fire fighter testing. , 2014, Applied ergonomics.

[2]  M. Verduin,et al.  A triaxial accelerometer for the assessment of daily physical activity in relation to energy expenditure , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[3]  P. A. Jones,et al.  Modified electrode placement must be recorded when performing 12-lead electrocardiograms , 2005, Postgraduate Medical Journal.

[4]  Dinesh John,et al.  Validation of the Fitbit wireless activity tracker for prediction of energy expenditure. , 2015, Journal of physical activity & health.

[5]  K. Albouaini,et al.  Cardiopulmonary exercise testing and its application , 2007, Postgraduate Medical Journal.

[6]  V. Rankovic,et al.  Mathematical analysis of the heart rate performance curve during incremental exercise testing. , 2011, Acta physiologica Hungarica.

[7]  Guang-Zhong Yang,et al.  Predicting Free-Living Energy Expenditure Using a Miniaturized Ear-Worn Sensor: An Evaluation Against Doubly Labeled Water , 2014, IEEE Transactions on Biomedical Engineering.

[8]  Charles E Matthews,et al.  The effect of social desirability and social approval on self-reports of physical activity. , 2005, American journal of epidemiology.

[9]  K. Wasserman.  Diagnosing cardiovascular and lung pathophysiology from exercise gas exchange. , 1997, Chest.

[10]  P. Bifulco,et al.  A mobile EEG system with dry electrodes , 2008, 2008 IEEE Biomedical Circuits and Systems Conference.

[11]  U. Wisløff,et al.  Accuracy of Heart Rate Watches: Implications for Weight Management , 2016, PloS one.

[12]  Stephen J. Redmond,et al.  Techniques for measuring energy expenditure with portable devices , 2013, IEEE 2013 Tencon - Spring.

[13]  I. Feurer,et al.  Energy Expenditure in Malnourished Cancer Patients , 1983, Annals of surgery.

[14]  Heart Rate, Blood Pressure, and Oxygen Consumption during Orthopaedic Rehabilitation Exercise. , 1987, The Journal of orthopaedic and sports physical therapy.

[15]  Judith Wylie-Rosett,et al.  Weight management through lifestyle modification for the prevention and management of type 2 diabetes: rationale and strategies: a statement of the American Diabetes Association, the North American Association for the Study of Obesity, and the American Society for Clinical Nutrition. , 2004, Diabetes care.

[16]  T. Scherstén,et al.  Energy balance and body composition in cancer patients. , 1978, Cancer research.

[17]  Shinsuke Hara,et al.  VO2 estimation using 6-axis motion sensing data , 2016, 2016 10th International Symposium on Medical Information and Communication Technology (ISMICT).

[18]  K. Pfeifer,et al.  [Multiple sclerosis and exercise : effects of physical activity on the immune system]. , 2009, Der Nervenarzt.

[19]  Marc T. Hamilton,et al.  Role of Low Energy Expenditure and Sitting in Obesity, Metabolic Syndrome, Type 2 Diabetes, and Cardiovascular Disease , 2007, Diabetes.

[20]  A. Melcher,et al.  Exercise energy expenditure in extreme obesity: influence of ergometry type and weight loss. , 1978, Scandinavian journal of clinical and laboratory investigation.

[21]  D. Hosmer,et al.  Maximal oxygen intake and nomographic assessment of functional aerobic impairment in cardiovascular disease. , 1973, American heart journal.

[22]  Alberto G. Bonomi,et al.  Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life , 2011, IEEE Transactions on Biomedical Engineering.

[23]  J. Skyler,et al.  Algorithms for Adjustment of Insulin Dosage by Patients Who Monitor Blood Glucose , 1981, Diabetes Care.

[24]  L. Epstein,et al.  Determinants of physical activity in obese children assessed by accelerometer and self-report. , 1996, Medicine and science in sports and exercise.

[25]  Ali Yalfani,et al.  The long-term benefits of cardiac rehabilitation on depression, anxiety, physical activity and quality of life. , 2010, Journal of clinical nursing.

[26]  J. Webster,et al.  Estimation of energy expenditure by a portable accelerometer. , 1983, Medicine and science in sports and exercise.

[27]  H. Zisser,et al.  Exercise and diabetes. , 2011, International journal of clinical practice. Supplement.

[28]  K. Pfeifer,et al.  Multiple Sklerose und Sport , 2009, Der Nervenarzt.

[29]  E. L. Rosado,et al.  Energy Expenditure Measured by Indirect Calorimetry in Obesity , 2013 .

[30]  M. Lambert,et al.  Autonomic Control of Heart Rate during and after Exercise , 2008, Sports medicine.

[31]  J. Woo,et al.  The standard oxygen consumption value equivalent to one metabolic equivalent (3.5 ml/min/kg) is not appropriate for elderly people , 2004, International journal of food sciences and nutrition.

[32]  Robert X. Gao,et al.  Multisensor Data Fusion for Physical Activity Assessment , 2012, IEEE Transactions on Biomedical Engineering.

[33]  Q. Tang,et al.  Weight loss and resting energy expenditure in male patients with newly diagnosed esophageal cancer. , 2013, Nutrition.

[34]  J. Naughton,et al.  Physical activity and the prevention of coronary heart disease. , 1972, Preventive medicine.

[35]  Torsten Lehmann,et al.  Open platform, eight-channel, portable bio-potential and activity data logger for wearable medical device development , 2015 .

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

[37]  H C Kemper,et al.  Tracking of activity and fitness and the relationship with cardiovascular disease risk factors. , 2000, Medicine and science in sports and exercise.

[38]  K. Laws,et al.  Physical activity and mental health in a student population , 2010, Journal of mental health.

[39]  Glen P. Kenny,et al.  Physical Activity/Exercise and Type 2 Diabetes , 2006, Diabetes Care.

[40]  F. Yasuma,et al.  Respiratory sinus arrhythmia. A phenomenon improving pulmonary gas exchange and circulatory efficiency. , 1996, Circulation.

[41]  S. Fowler,et al.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. , 2002 .

[42]  Christopher J. Dondzila,et al.  Comparative accuracy of fitness tracking modalities in quantifying energy expenditure , 2016, Journal of medical engineering & technology.