patients is usually performed using a three-dimensional motion analysis system and a force plate in the laboratory. However, these methods are not used more frequently in clinical practice because of complications in measurement and data processing ( Krause et al., 2015 ). On the other hand, accelerometers
Yoshifumi Kijima, Ryoji Kiyama, Masaki Sekine, Toshiyo Tamura, Toshiro Fujimoto, Tetsuo Maeda and Tadasu Ohshige
Jonathan Sinclair, Sarah J. Hobbs, Laurence Protheroe, Christopher J. Edmundson and Andrew Greenhalgh
Biomechanical analysis requires the determination of specific foot contact events. This is typically achieved using force platform information; however, when force platforms are unavailable, alternative methods are necessary. A method was developed for the determination of gait events using an accelerometer mounted to the distal tibia, measuring axial accelerations. The aim of the investigation was to determine the efficacy of this method. Sixteen participants ran at 4.0 m/s ±5%. Synchronized tibial accelerations and vertical ground reaction forces were sampled at 1000 Hz as participants struck a force platform with their dominant foot. Events determined using the accelerometer, were compared with the corresponding events determined using the force platform. Mean errors of 1.68 and 5.46 ms for average and absolute errors were observed for heel strike and of –3.59 and 5.00 ms for toe-off. Mean and absolute errors of 5.18 and 11.47 ms were also found for the duration of the stance phase. Strong correlations (r = .96) were also observed between duration of stance obtained using the two different methods. The error values compare favorably to other alternative methods of predicting gait events. This suggests that shank-mounted accelerometers can be used to accurately and reliably detect gait events.
Christopher A. Bailey and Patrick A. Costigan
The step-up-and-over test has been used successfully to examine knee function after knee injury. Knee function is quantified using the following variables extracted from force plate data: the maximal force exerted during the lift, the maximal impact force at landing, and the total time to complete the step. For various reasons, including space and cost, it is unlikely that all clinicians will have access to a force plate. The purpose of the study was to determine if the step-up-and-over test could be simplified by using an accelerometer. The step-up-and-over test was performed by 17 healthy young adults while being measured with both a force plate and a 3-axis accelerometer mounted at the low back. Results showed that the accelerometer and force plate measures were strongly correlated for all 3 variables (r = .90–.98, Ps < .001) and that the accelerometer values for the lift and impact indices were 6–7% higher (Ps < .01) and occurred 0.07–0.1 s later than the force plate (Ps < .05). The accelerometer returned values highly correlated to those from a force plate. Compared with a force plate, a wireless, 3-axis accelerometer is a less expensive and more portable system with which to measure the step-up-and-over test.
Dylan Kobsar, Chad Olson, Raman Paranjape and John M. Barden
A single triaxial accelerometer has the ability to collect a large amount of continuous gait data to quantitatively assess the control of gait. Unfortunately, there is limited information on the validity of gait variability and fractal dynamics obtained from this device. The purpose of this study was to test the concurrent validity of the variability and fractal dynamic measures of gait provided by a triaxial accelerometer during a continuous 10 minute walk in older adults. Forty-one healthy older adults were fitted with a single triaxial accelerometer at the waist, as well as a criterion footswitch device before completing a ten minute overground walk. The concurrent validity of six outcome measures was examined using intraclass correlation coefficients (ICC) and 95% limits of agreement. All six dependent variables measured by the accelerometer displayed excellent agreement with the footswitch device. Mean parameters displayed the highest validity, followed by measures of variability and fractal dynamics in stride times and measures of variability and fractal dynamics in step times. These findings suggest that an accelerometer is a valid and unique device that has the potential to provide clinicians with valid quantitative data for assessing their clients’ gait.
Veronika van der Wardt, Jennie E. Hancox, Clare Burgon, Rupinder Bajwa, Sarah Goldberg and Rowan H. Harwood
relies on people’s memories, although, if they are completed on a daily basis, activities might be easier to recall. PA monitors (pedometers and accelerometers) have been used in people with MCI or dementia to support engagement in PA ( Vidoni et al., 2016 ), as well as to measure PA levels in randomized
Meredith C. Peddie, Matthew Reeves, Millie K. Keown, Tracy L. Perry and C. Murray Skeaff
breaks of the appropriate intensity could be challenging in free-living studies as currently it would appear that the optimal intensity sits somewhere between the established cut-offs for light and moderate intensity activity identified for accelerometer data ( Freedson, Melanson, & Sirard, 1998
Anna Gabriela Silva Vilela Ribeiro, Rozangela Verlengia, Maria Rita Marques de Oliveira, Matheus Valério Almeida Oliveira, Idico Luiz Pellegrinotti and Alex Harley Crisp
has an average annual temperature of 23.9 °C, varying between 12 °C and 31 °C throughout the year. The sample size calculation was based on the total population of older adults in Piracicaba ( N = 45,554), 85% estimated prevalence of physical inactivity by accelerometer, a sampling error of 5%, and a
Jonathan M. Williams, Michael Gara and Carol Clark
environments and incur increased costs, limiting their uptake into routine practice. Therefore, novel methods for quantifying balance in clinical practice are needed. Accelerometers have quantified balance across a range of disease states and task conditions. 3 – 6 Accelerometers commonly mounted on the low
Tatiana Plekhanova, Alex V. Rowlands, Tom Yates, Andrew Hall, Emer M. Brady, Melanie Davies, Kamlesh Khunti and Charlotte L. Edwardson
measures daily sleep–wake cycles ( Berger et al., 2008 ; Martin & Hakim, 2011 ). However, the data are in the form of manufacturer-specific activity “counts” over a specific time window, making it difficult to compare the data with different accelerometer brands ( van Hees et al., 2015 ). Therefore, there
Stephen Hunter, Andrei Rosu, Kylie D. Hesketh, Ryan E. Rhodes, Christina M. Rinaldi, Wendy Rodgers, John C. Spence and Valerie Carson
questionnaire and were provided an accelerometer for their child to wear, along with a verbal and written overview of the wear protocol. A total of 257 out of 491 eligible families agreed to participate in this study (52% participation rate). Reasons for not participating have been published elsewhere ( 32