Recent Advances in Free-Living Physical Activity Monitoring: A Review

Andre, David; Wolf, Donna

doi:10.1177/193229680700100522

Cited by 57 publications

(58 citation statements)

References 41 publications

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“…Portable metabolic cart and doubly labeled water were two of the most commonly used criterion measures for evaluating the performance of activity monitors in quantifying the energy cost. The portable metabolic cart is a wearable device, but a facial mask is needed to collect gas samples, which limits the types of activities people can perform [57], whereas doubly labeled water requires urine or saliva specimens before and after drinking an initial dose of 2 H 2 18 O [57]. The portable metabolic cart provides breath-by-breath energy cost, while the doubly labeled water provides an overall energy cost over the entire monitoring period.…”

Section: Limitations Of Evaluation Studiesmentioning

confidence: 99%

Validity of activity monitors in wheelchair users: A systematic review

et al. 2016

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Abstract-Assessing physical activity (PA) in manual wheelchair users (MWUs) is challenging because of their different movement patterns in comparison to the ambulatory population. The aim of this review was to investigate the validity of portable monitors in quantifying PA in MWUs. A systematic literature search was performed. The data source was full reports of validation and evaluation studies in peer-reviewed journals and conference proceedings. Eligible articles between January 1, 1999, and September 18, 2015, were identified in three databases: PubMed, Institute of Electrical and Electronics Engineers, and Scopus. A total of 164 articles (158 from the databases and 6 from the citation/reference tracking) were identified, and 29 met the eligibility criteria. Two investigators independently extracted the characteristics from each selected article following a predetermined protocol and completed seven summary tables describing the study characteristics and key outcomes. In the identified studies, the monitors were used to assess three types of PA measures: energy cost, user movement, and wheelchair movement. The customized algorithms/ monitors did not estimate energy cost in MWUs as well as the commercial monitors did in the ambulatory population; however, they showed fair accuracy in measuring both wheelchair and user movements.

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Section: Limitations Of Evaluation Studiesmentioning

confidence: 99%

Validity of activity monitors in wheelchair users: A systematic review

et al. 2016

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“…8 Since obesity and type 2 diabetes mellitus (T2D), 2 major disorders of whole body energy balance, continue to rise worldwide, most research to-date regarding physical activity capture device use has been pursued in these 2 disorders. 9,10 T2D is characterized by hyperglycemia for a significant proportion of the day with the majority of such subjects having limited hypoglycemia until the disorder is quite advanced in duration or associated with comorbidities. 11 Since weight control is one of the main clinical end points in both obesity and T2D, energy expenditure tracking in such patients requires devices and output quite different from those for T1D as discussed above and below.…”

Section: Special Sectionmentioning

confidence: 99%

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Dadlani

Levine

McCrady-Spitzer

et al. 2015

J Diabetes Sci Technol

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Type 1 diabetes (T1D) is characterized by complete or near complete absence of endogenous insulin secretion resulting in the need to deliver exogenous insulin in an individualized, precise manner.1 Current clinically approved technologies to replace insulin result in unacceptable risk for hypoglycemia, hyperglycemia, and glycemic variability (GV).2 Changes in plasma glucose concentration are more pronounced in T1D, occur rapidly and are related to food intake, physical activity and imprecise insulin delivery. The maturation of technologies such as continuous glucose monitoring (CGM), continuous subcutaneous insulin infusion (CSII) or insulin pump, rapid acting insulin analogs and closed-loop control (CLC) algorithms that deliver insulin based on CGM data processing has resulted in CLC therapy becoming an area of active research with rapid therapeutic translation to clinical practice. 4 Current CLC studies show significant improvement in hypoglycemia and a bigger burden of hyperglycemia relative to time spent in hypoglycemic range. 4,5 Occurrence of hyper and hypoglycemia with current CLC, the burden associated with current CLC and limitations of eligible populations to use current technologies indicate the need for further innovation. Important variables in this context with potentially significant effect sizes are physical activity and meals. Significant efforts have been made to model the aforementioned parameters and understand their effect on glucose-insulin dynamics by incorporating/adapting them into CLC simulators. 6,7 Even though the day to day effect of physical activity on glucose status poses major challenges for T1D, limited research in this area has been conducted. 8 Since obesity and type 2 diabetes mellitus (T2D), 2 major disorders of whole body energy balance, continue to rise worldwide, most research to-date regarding physical activity capture device use has been pursued in these 2 disorders.9,10 T2D is characterized by hyperglycemia for a significant proportion of the day with the majority of such subjects having limited hypoglycemia AbstractPhysical activity is an important determinant of glucose variability in type 1 diabetes (T1D). It has been incorporated as a nonglucose input into closed-loop control (CLC) protocols for T1D during the last 4 years mainly by 3 research groups in single center based controlled clinical trials involving a maximum of 18 subjects in any 1 study. Although physical activity data capture may have clinical benefit in patients with T1D by impacting cardiovascular fitness and optimal body weight achievement and maintenance, limited number of such studies have been conducted to date. Clinical trial registries provide information about a single small sample size 2 center prospective study incorporating physical activity data input to modulate closed-loop control in T1D that are seeking to build on prior studies. We expect an increase in such studies especially since the NIH has expanded support of this type of research with additional grants starting in the second hal...

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“…Accordingly, it is important to first survey the connection between skin hydration and the ECG signal. To quantitatively evaluate a change in ECG amplitude that is dependent on the degree of skin hydration, the root-mean-square (RMS) value was calculated using formula (1). We then compared the RMS of data acquired by using the Ag-AgCl electrode with that of data acquired using the textile electrode.…”

Section: Skin Hydration Measurementmentioning

confidence: 99%

“…Thus, bio-signal measurement technology, which involves measurement of bio-parameters during exercise, is being rapidly introduced to the field of sports science [1]. The application of bio-signal measurement technology to the field of sports science offers the ability to prevent medical accidents and protect health status during exercise.…”

Section: Introductionmentioning

confidence: 99%

Optimization methods for improving the performance of heart rate detection by a wearable ECG system during high-intensity exercise

2011

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Purpose Wearable electrocardiogram (ECG) systems are exposed to more noises than the general ECG systems, because of the high impedance between electrodes and the skin and the need to acquire ECG data during exercise or in daily life. The purpose of this study was to enhance heart rate detection by optimizing electrode and signal processing in a wearable system during high-intensity exercise. Methods To create an optimal electrode condition, we quantitatively measured the change in noise according to a change in pattern of textile electrodes by using 3 textile electrodes with the same material quality but different patterns. We also measured the degree of skin hydration by using an MPA5 (CK Electronics, Germany) to obtain the optimal condition between electrodes and skin. To accurately detect the QRS complex, use of an improved algorithm based on a wavelet, which has strong noise tolerance, was suggested. Results We obtained root-mean-square (RMS) values that were expected to be similar to those measured with the AgAgCl electrode at the point of >120% of skin hydration. The QRS complex detection rate of the wavelet method that was suggested in this study was compared to that of an adaptive filter and mathematical morphology operator. We used the data collected during actual exercise performed at 15 km/h. The QRS complex detection rate of the proposed algorithm was 99.9%. Conclusions Through optimization of the wearable system that was suggested in this study, collection of a more accurate heart rate value is expected. In addition, the influence of noise could be minimized in the wearable system.

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Recent Advances in Free-Living Physical Activity Monitoring: A Review

Cited by 57 publications

References 41 publications

Validity of activity monitors in wheelchair users: A systematic review

Validity of activity monitors in wheelchair users: A systematic review

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Optimization methods for improving the performance of heart rate detection by a wearable ECG system during high-intensity exercise

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