Not all sensors are created equal: a framework for evaluating human performance measurement technologies.

Recent years have witnessed an explosion in the number of wearable sensing devices and associated apps that target a wide range of biomedical metrics, from actigraphy to glucose monitoring to lung function. This offers big opportunities for achieving scale in the use of such devices in application contexts such as telehealth, human performance and behaviour research and digitally enabled clinical trials. However, this increased availability and choice of sensors also brings with it a great challenge in optimising the match between the sensor and a specific application context.

The Burden of a Remote Trial in a Nursing Home Setting: Qualitative Study.

Background: Despite an aging population, older adults are typically underrecruited in clinical trials, often because of the perceived burden associated with participation, particularly travel associated with clinic visits. Conducting a clinical trial remotely presents an opportunity to leverage mobile and wearable technologies to bring the research to the patient. However, the burden associated with shifting clinical research to a remote site requires exploration.

Context focused older adult mobility and gait assessment.

This paper presents an initial overview of insights gained into how older adults mobilize in the home and community, based on data from inertial sensors which were worn by study participants over a 7-day period. The addition of a wearable camera provided additional contextual information which can be used to assess mobility and understand the factors that influence it in the free living environment. Seven days of data collected from a group of older adults who had experienced one or more falls in the previous six months was compared to that of a control group with no history of falling.

Context aware falls risk assessment: A case study comparison.

This paper describes three retrospective case studies to illustrate the potential clinical value of a system capable of capturing objective gait metrics and environment data from older adults with a history of falls while they go about their daily lives. Participants in this study wore an inertial sensor above each ankle and a wearable camera around their neck for seven consecutive days. Selected metrics are presented to illustrate scenarios where the data collected by the system could be of clinical value.

Does external walking environment affect gait patterns?

The objective of this work is to develop an understanding of the relationship between mobility metrics obtained outside of the clinic or laboratory and the context of the external environment. Ten subjects walked with an inertial sensor on each shank and a wearable camera around their neck. They were taken on a thirty minute walk in which they mobilized over the following conditions; normal path, busy hallway, rough ground, blind folded and on a hill.