BackgroundWalking ability is an important prerequisite for activity, social participation and independent living. While in most healthy adults, this ability can be assumed as given, limitations in walking ability occur with increasing age. Furthermore, slow walking speed is linked to several chronic conditions and overall morbidity. Measurements of gait parameters can be used as a proxy to detect functional decline and onset of chronic conditions. Up to now, gait characteristics used for this purpose are measured in standardized laboratory settings. There is some evidence, however, that long-term measurements of gait parameters in the living environment have some advantages over short-term laboratory measurements.MethodsWe evaluated cross-sectional data from an accelerometric sensor worn in a subgroup of 554 participants of the Berlin Aging Study II (BASE-II). Data from the two BASE-II age groups (age between 22–36 years and 60–79 years) were used for the current analysis of accelerometric data for a minimum of two days and a maximum of ten days were available. Real world walking speed, number of steps, maximum coherent distance and total distance were derived as average data per day. Linear regression analyses were performed on the different gait parameters in order to identify significant determinants. Additionally, Mann-Whitney-U-tests were performed to detect sex-specific differences.ResultsAge showed to be significantly associated with real world walking speed and with the total distance covered per day, while BMI contributed negatively to the number of walking steps, maximum coherent distance and total distance walked. Additionally, sex was associated with walking steps. However, R2-values for all models were low. Overall, women had significantly more walking steps and a larger coherent distance per day when compared to men. When separated by age group, this difference was significant only in the older participants. Additionally, walking speed was significantly higher in women compared to men in the subgroup of older people.ConclusionsAge- and sex-specific differences have to be considered when objective gait parameters are measured, e.g. in the context of clinical risk assessment. For this purpose normative data, differentiating for age and sex would have to be established to allow reliable classification of long-term measurements of gait.

Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual’s recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient’s recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.

No abstract

Mobile accelerometry is more and more being used in clinical trials as a tool to measure outcomes related to physical activity. However, it is still difficult to integrate exercise therapy in controlled clinical trials. We want to explore the option to use a unified platform to both measure outcome and prescribe and monitor exercise therapy using the actibelt technology platform. We present a prototype based on the actibelt platform that allows to use the wearable device as a mouse controller for a large set of potentially interesting games. Playing an exergame a person is encouraged to increase its level of daily motion while engaging in an activity that is perceived as interesting and fun, thus, providing an intrinsic motivation. Studies suggest that exergaming can be compared to light or moderate physical activity considering the heart rate, oxygen consumption and energy expenditure.PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.929v1 | CC-BY 4.0 Open Access | rec: 25

Mobile accelerometry is more and more being used in clinical trials as a tool to measure outcomes related to physical activity. However, it is still difficult to integrate exercise therapy in controlled clinical trials. We want to explore the option to use a unified platform to both measure outcome and prescribe and monitor exercise therapy using the actibelt technology platform. We present a prototype based on the actibelt platform that allows to use the wearable device as a mouse controller for a large set of potentially interesting games. Playing an exergame a person is encouraged to increase its level of daily motion while engaging in an activity that is perceived as interesting and fun, thus, providing an intrinsic motivation. Studies suggest that exergaming can be compared to light or moderate physical activity considering the heart rate, oxygen consumption and energy expenditure.