Purpose The study aims were: 1) to develop transparent algorithms that use short segments of training data for predicting activity types; and 2) to compare prediction performance of proposed algorithms using single accelerometers and multiple accelerometers. Methods Sixteen participants (age, 80.6 yr (4.8 yr); BMI, 26.1 kg·m−2 (2.5 kg·m−2)) performed fifteen life-style activities in the laboratory, each wearing three accelerometers at the right hip, left and right wrists. Triaxial accelerometry data were collected at 80 Hz using Actigraph GT3X+. Prediction algorithms were developed, which, instead of extracting features, build activity specific dictionaries composed of short signal segments called movelets. Three alternative approaches were proposed to integrate the information from the multiple accelerometers. Results With at most several seconds of training data per activity, the prediction accuracy at the second-level temporal resolution was very high for lying, standing, normal/fast walking, and standing up from a chair (the median prediction accuracy ranged from 88.2% to 99.9% based on the single-accelerometer movelet approach). For these activities wrist-worn accelerometers performed almost as well as hip-worn accelerometers (the median difference in accuracy between wrist and hip ranged from −2.7% to 5.8%). Modest improvements in prediction accuracy were achieved by integrating information from multiple accelerometers. Discussion and conclusions It is possible to achieve high prediction accuracy at the secondlevel temporal resolution with very limited training data. To increase prediction accuracy from the simultaneous use of multiple accelerometers, a careful selection of integrative approaches is required.

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Background and Aims Fast and usual-paced 400m walking tests are often used to assess physical fitness or function, respectively, though it is not known how performance converges on these tests. This study aims to determine whether performance on the fast and usual-paced 400m walks varies based upon age and physical function. Methods Participants (26 men, 38 women aged 70–92) completed a fast and usual-paced 400m walk. The Short Physical Performance Battery was used to assess function (score range 0–12). Body mass index and health history were also assessed. Results Finish times for the fast and usual-paced 400m walks were 333.3 and 380.3 seconds, respectively (p<0.0001), and highly correlated (r =.88, P <.001). Higher functioning participants (SPPB >10) had greater differences between tests compared to lower functioning participants (SPPB ≤ 10) (52.9 vs. 26.2 seconds, p=0.005), as did younger participants (age <80) compared to those age 80 and older (56.8 vs. 32.8 seconds, p=0.003). Discussion Older and lower functioning participants had greater convergence on the fast and usual-paced 400m walks. Potentially some of these lower functioning and older adults may have already performing at their maximal capacity during the usual-paced walk, while the younger and higher functioning participants were able to walk substantially faster when asked. Conclusions Choice of walking test should consider the age and functional capacity of the population as well as whether function or fitness is of interest.

CKD is associated with changes in sensory and autonomic nerve function, even after adjustment for demographics and comorbidities, including diabetes. Longitudinal studies in CKD are needed to determine the contribution of nerve impairments to clinically important outcomes.