A systematic review and meta-analysis of outcome measures to assess postural control in older adults who undertake exergaming

Exergaming has been shown to be an effective tool to improve postural control (PC) in older community-dwelling individuals. The outcome measures (OMs) used to assess PC are varied and this could limit the estimation of the effectiveness of the intervention. This systematic review and meta-analysis aims to explore the OMs currently used to assess PC in exergaming interventions, for healthy elderly individuals aged over 60 years. The literature search was conducted across five databases (CINAHL, EMBASE, PubMed, ISI, SPORTdiscus and Science Direct) using a range of search terms and combinations relating to exergaming, balance, exercise, falls and elderly. Quality assessment was conducted using the PEDro Scale and a custom-made quality assessment tool. Eleven trials were included in the meta-analysis, with a mean (SD) PEDro score of 5.36 (1.57). Primary and secondary OMs showed small effects in favour of alternative training modes, although these effects were statistically insignificant for all primary OMs. Tertiary OMs could not be included in the meta-analysis due to varying output parameters from different instruments. Heterogeneity remained high across trials and no studies performed long-term follow-up. Exergaming is a potential alternative to PC training, although still in its infancy. Strong and well-designed RCTs are needed, targeting specific populations aged over 60 years. Variability in instrumented OMs prevents generalisation of results. Technological improvements may provide data not currently available from clinical and laboratory-based methods, and may allow PC to be assessed more realistically and specifically in relation to a population’s activities of daily living, though this remains a new area of research

Application of data fusion techniques and technologies for wearable health monitoring

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market

These legs were made for propulsion: advancing the diagnosis and treatment of post-stroke propulsion deficits

Advances in medical diagnosis and treatment have facilitated the emergence of precision medicine. In contrast, locomotor rehabilitation for individuals with acquired neuromotor injuries remains limited by the dearth of (i) diagnostic approaches that can identify the specific neuromuscular, biomechanical, and clinical deficits underlying impaired locomotion and (ii) evidence-based, targeted treatments. In particular, impaired propulsion by the paretic limb is a major contributor to walking-related disability after stroke; however, few interventions have been able to target deficits in propulsion effectively and in a manner that reduces walking disability. Indeed, the weakness and impaired control that is characteristic of post-stroke hemiparesis leads to heterogeneous deficits that impair paretic propulsion and contribute to a slow, metabolically-expensive, and unstable gait. Current rehabilitation paradigms emphasize the rapid attainment of walking independence, not the restoration of normal propulsion function. Although walking independence is an important goal for stroke survivors, independence achieved via compensatory strategies may prevent the recovery of propulsion needed for the fast, economical, and stable gait that is characteristic of healthy bipedal locomotion. We posit that post-stroke rehabilitation should aim to promote independent walking, in part, through the acquisition of enhanced propulsion. In this expert review, we present the biomechanical and functional consequences of post-stroke propulsion deficits, review advances in our understanding of the nature of post-stroke propulsion impairment, and discuss emerging diagnostic and treatment approaches that have the potential to facilitate new rehabilitation paradigms targeting propulsion restoration.R01 AG067394 - NIA NIH HHS; R01 HD095975 - NICHD NIH HHS; K01 HD079584 - NICHD NIH HHSPublished versio

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Centre of pressure estimation during walking using only inertial-measurement units and end-to-end statistical modelling

Estimation of the centre of pressure (COP) is an important part of the gait analysis, for example, when evaluating the functional capacity of individuals affected by motor impairment. Inertial measurement units (IMUs) and force sensors are commonly used to measure gait characteristic of healthy and impaired subjects. We present a methodology for estimating the COP solely from raw gyroscope, accelerometer, and magnetometer data from IMUs using statistical modelling. We demonstrate the viability of the method using an example of two models: a linear model and a non-linear Long-Short-Term Memory (LSTM) neural network model. Models were trained on the COP ground truth data measured using an instrumented treadmill and achieved the average intra-subject root mean square (RMS) error between estimated and ground truth COP of 12.3mm and the average inter-subject RMS error of 23.7mm which is comparable or better than similar studies so far. We show that the calibration procedure in the instrumented treadmill can be as short as a couple of minutes without the decrease in our model performance. We also show that the magnetic component of the recorded IMU signal, which is most sensitive to environmental changes, can be safely dropped without a significant decrease in model performance. Finally, we show that the number of IMUs can be reduced to five without deterioration in the model performance.Comment: 21 page

Mechanisms of Stability and Energy Expenditure in Human Locomotion.

Although humans normally walk with both stability and energy economy, either feature may be challenging for persons with disabilities. For example, in patients with lower-limb amputation, falling is pervasive, and may lead to activity avoidance. Similarly, energy expenditure is higher than for healthy subjects and may deter patients from walking, reducing mobility. A better understanding of the fundamental principles of stability and economy could lead to better prostheses that increase quality of life for patients. When designing a mechanism to assist or mimic human gait, such as orthoses or walking robots, the stability and economy of the resulting gait should be considered. To further our understanding of these fundamental principles of gait, I explore a lesser known balance mechanism, foot heading, as well as the role of muscle force production costs in gait. To investigate the stabilizing role of foot heading, I first characterize a method of measuring natural human gait variability outside of lab environments using foot mounted inertial sensors. Accuracy is found comparable to motion capture, while allowing capture of gait in natural environments. Then, using both a simple model of walking, and a variability analysis of human walking, I present evidence that humans stabilize gait laterally by altering foot heading step-to-step. I then consider the metabolic cost of force production in human locomotion. First, an optimization study of a simple model of locomotion shows that force fluctuation costs have a stronger role in determining gait than force amplitude costs. I then illustrate the connection between force fluctuation and a cost for calcium pumping in muscles using a simple muscle model. Finally, a human subject experiment altering force fluctuation in walking demonstrates the higher metabolic cost of fluctuating forces. While human locomotion is a complex activity involving many muscles, sensory systems, and neural circuitry, we can use basic mechanical models to study underlying principles of gait. A better understanding of stability and economy could have applications to many fields involving locomotion, such as the diagnosis of fall-risk in elderly subjects, the development of rehabilitation techniques, the design of prostheses, and the creation of robust and practical walking machines.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108908/1/jrebula_1.pd