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Does external walking environment affect gait patterns?
2014-08-30, Patterson, Matthew, Whelan, Darragh, Reginatto, Brenda, Caprani, Niamh, Caulfield, Brian, et al.
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. Stride time, stride time variability, stance time and peak shank rotation rate during swing were calculated using previously published algorithms. Stride time was significantly different between several of the conditions. Technological advances mean that gait variables can now be captured as patients go about their daily lives. The results of this study show that the external environment has a significant impact on the quality of gait metrics. Thus, context of external walking environment is an important consideration when analyzing ambulatory gait metrics from the unsupervised home and community setting.
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Not All Sensors are Created Equal: A Framework for Evaluating Human Performance Measurement technologies
2019-02-14, Caulfield, Brian, Reginatto, Brenda, Slevin, Patrick
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. There is a need for a structured approach to first refining the requirements for a specific application, and then evaluating the available devices against those requirements. In this paper we will outline the main features of such an evaluation framework that has been developed with input from stakeholders in academic, clinical and industry settings.
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The Burden of a Remote Trial in a Nursing Home Setting: Qualitative Study
2018-06-19, Donnelly, Susie, Reginatto, Brenda, Kearns, Oisin, Caulfield, Brian, et al.
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. While a remote trial may reduce patient burden, the extent to which this shifts burden on the other stakeholders needs to be investigated. Objective: The aim of this study was to explore the burden associated with a remote trial in a nursing home setting on both staff and residents. Methods: Using results from a grounded analysis of qualitative data, this study explored and characterized the burden associated with a remote trial conducted in a nursing home in Dublin, Ireland. A total of 11 residents were recruited to participate in this trial (mean age: 80 years; age range: 67-93 years). To support research activities, we also recruited 10 nursing home staff members, including health care assistants, an activities co-ordinator, and senior nurses. This study captured the lived experience of this remote trial among staff and residents and explored the burden associated with participation. At the end of the trial, a total of 6 residents and 8 members of staff participated in semistructured interviews (n=14). They reviewed clinical data generated by mobile and wearable devices and reflected upon their trial-related experiences. Results: Staff reported extensive burden in fulfilling their roles and responsibilities to support activities of the trial. Among staff, we found eight key characteristics of burden: (1) comprehension, (2) time, (3) communication, (4) emotional load, (5) cognitive load, (6) research engagement, (7) logistical burden, and (8) product accountability. Residents reported comparatively less burden. Among residents, we found only four key characteristics of burden: (1) comprehension, (2) adherence, (3) emotional load, and (4) personal space. Conclusions: A remote trial in a nursing home setting can minimize the burden on residents and enable inclusive participation. However, it arguably creates additional burden on staff, particularly where they have a role to play in locally supporting and maintaining technology as part of data collection. Future research should examine how to measure and minimize the burden associated with data collection in remote trials.