Research demonstrates that physical activity beneficially influences brain function, quality of life and reduces cardiovascular diseases. Therefore, many projects and technical developments aim to promote physical activity. As a result of the ''quantified self''-movement, a great number of wearable technologies, which are mainly developed for a younger target group, emerged on the market. However, there is a lack of scientific studies to establish which systems are suitable for older adults and there is still little known about seniors' needs and preferences regarding fitness trackers. In this crossover-designed usability study, 20 older adults aged over 60 took part. In the study, all participants were requested to rate the usability of five of the most widely used fitness trackers (Nike FuelBand, Jawbone Up, Fitbit Flex, Garmin vivofit, Sony SmartBand) and were asked about their preferences. Participants had to rate its ergonomic features such as handling, material and design. Overall, the fitness trackers differ a lot in tracking features, design, usability and acceptance of the seniors. We present an aggregated list of requirements for the ''ideal'' activity tracker for older adults. The results seem to be of high interest for developers, but also for scientists to choose appropriate sensors for technology-based interventions that may promote physical activity.

While previous attempts to train self-control in humans have frequently failed, we set out to train response inhibition using computer-game elements. We trained older adults with a newly developed game-based inhibition training on a tablet for two months and compared them to an active and passive control group. Behavioural effects reflected in shorter stop signal response times that were observed only in the inhibition-training group. This was accompanied by structural growth in cortical thickness of right inferior frontal gyrus (rIFG) triangularis, a brain region that has been associated with response inhibition. The structural plasticity effect was positively associated with time spent on the training-task and predicted the final percentage of successful inhibition trials in the stop task. The data provide evidence for successful trainability of inhibition when game-based training is employed. The results extend our knowledge on game-based cognitive training effects in older age and may foster treatment research in psychiatric diseases related to impulse control.

Despite its paramount importance for manifold use cases (e.g., in the health care industry, sports, rehabilitation and fitness assessment), sufficiently valid and reliable gait parameter measurement is still limited to high-tech gait laboratories mostly. Here, we demonstrate the excellent validity and test–retest repeatability of a novel gait assessment system which is built upon modern convolutional neural networks to extract three-dimensional skeleton joints from monocular frontal-view videos of walking humans. The validity study is based on a comparison to the GAITRite pressure-sensitive walkway system. All measured gait parameters (gait speed, cadence, step length and step time) showed excellent concurrent validity for multiple walk trials at normal and fast gait speeds. The test–retest-repeatability is on the same level as the GAITRite system. In conclusion, we are convinced that our results can pave the way for cost, space and operationally effective gait analysis in broad mainstream applications. Most sensor-based systems are costly, must be operated by extensively trained personnel (e.g., motion capture systems) or—even if not quite as costly—still possess considerable complexity (e.g., wearable sensors). In contrast, a video sufficient for the assessment method presented here can be obtained by anyone, without much training, via a smartphone camera.