Commercially available pedometers: considerations for accurate step counting

Melanson, Edward L.; Knoll, J R.; Bell, Melanie L.; Donahoo, William T.; Hill, James O.; Nysse, Lana J.; Lanningham-Foster, Lorraine; Peters, John C.; Levine, James A.

doi:10.1016/j.ypmed.2004.01.032

Cited by 234 publications

(236 citation statements)

References 20 publications

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“…Also with very high data acquisition rates, the internal buffers on the electronic systems need to be large (adding unnecessary cost). [48][49][50] Overall the rate of data gathering needs to be appropriate for the signal being traced. When walking briskly, a full stride (right and left heel strike) occurs about once per second which is 2 Hz.…”

Section: Choice Of Accelerometermentioning

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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Section: Choice Of Accelerometermentioning

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

View full text Add to dashboard Cite

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“…Furthermore, greater body mass index, waist circumference and tilt angle were shown to reduce the step count accuracy of spring-levered pedometers. 31,32 Thus, concerns have been raised about the use of this type of pedometer in obese Activity monitoring and health AG Bonomi and KR Westerterp subjects, who also have a tendency to ambulate at slower speeds. 31,33 Inertial and spring-levered pedometers have distinctive characteristics that produce a different degree of accuracy.…”

Section: How To Measure Physical Activitymentioning

confidence: 99%

Advances in physical activity monitoring and lifestyle interventions in obesity: a review

Bonomi

Westerterp

2011

Int J Obes

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Obesity represents a strong risk factor for developing chronic diseases. Strategies for disease prevention often promote lifestyle changes encouraging participation in physical activity. However, determining what amount of physical activity is necessary for achieving specific health benefits has been hampered by the lack of accurate instruments for monitoring physical activity and the related physiological outcomes. This review aims at presenting recent advances in activity-monitoring technology and their application to support interventions for health promotion. Activity monitors have evolved from step counters and measuring devices of physical activity duration and intensity to more advanced systems providing quantitative and qualitative information on the individuals' activity behavior. Correspondingly, methods to predict activity-related energy expenditure using bodily acceleration and subjects characteristics have advanced from linear regression to innovative algorithms capable of determining physical activity types and the related metabolic costs. These novel techniques can monitor modes of sedentary behavior as well as the engagement in specific activity types that helps to evaluate the effectiveness of lifestyle interventions. In conclusion, advances in activity monitoring have the potential to support the design of response-dependent physical activity recommendations that are needed to generate effective and personalized lifestyle interventions for health promotion.

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“…The SW pedometer range has been shown to accurately detect steps in controlled laboratory (Le Masurier and Tudor-Locke 2003;Swartz et al 2003;Melanson et al 2004) and freeliving conditions (Le Masurier et al 2004;Schneider et al 2004) and has consequently been employed in numerous free-living activity studies (Chan et al 2004;Tudor-Locke et al 2004b;Hornbuckle et al 2005). The pedometer accurately assesses walking activity of all BMI classifications (Swartz et al 2003).…”

Section: Physical Activity Assessmentmentioning

confidence: 99%