Now showing 1 - 7 of 7
  • Publication
    It's Not as Simple as Just Looking at One Chart: A Qualitative Study Exploring Clinicians Opinions on Various Visualisation Strategies to Represent Longitudinal Actigraphy Data
    Background: Data derived from wearable activity trackers may provide important clinical insights into disease progression and response to intervention, but only if clinicians can interpret it in a meaningful manner. Longitudinal activity data can be visually presented in multiple ways, but research has failed to explore how clinicians interact with and interpret these visualisations. In response, this study developed a variety of visualisations to understand whether alternative data presentation strategies can provide clinicians with meaningful insights into patient’s physical activity patterns. Objective: To explore clinicians’ opinions on different visualisations of actigraphy data. Methods: Four visualisations (stacked bar chart, clustered bar chart, linear heatmap and radial heatmap) were created using Matplotlib and Seaborn Python libraries. A focus group was conducted with 14 clinicians across 2 hospitals. Focus groups were audio-recorded, transcribed and analysed using inductive thematic analysis. Results: Three major themes were identified: (1) the importance of context, (2) interpreting the visualisations and (3) applying visualisations to clinical practice. Although clinicians saw the potential value in the visualisations, they expressed a need for further contextual information to gain clinical benefits from them. Allied health professionals preferred more granular, temporal information compared to doctors. Specifically, physiotherapists favoured heatmaps, whereas the remaining members of the team favoured stacked bar charts. Overall, heatmaps were considered more difficult to interpret. Conclusion: The current lack of contextual data provided by wearables hampers their use in clinical practice. Clinicians favour data presented in a familiar format and yet desire multi-faceted filtering. Future research should implement user-centred design processes to identify ways in which all clinical needs can be met, potentially using an interactive system that caters for multiple levels of granularity. Irrespective of how data is displayed, unless clinicians can apply it in a manner that best supports their role, the potential of this data cannot be fully realised.
      28Scopus© Citations 6
  • Publication
    The Importance of Real-World Validation of Machine Learning Systems in Wearable Exercise Biofeedback Platforms: A Case Study
    Machine learning models are being utilized to provide wearable sensor-based exercise biofeedback to patients undertaking physical therapy. However, most systems are validated at a technical level using lab-based cross validation approaches. These results do not necessarily reflect the performance levels that patients and clinicians can expect in the real-world environment. This study aimed to conduct a thorough evaluation of an example wearable exercise biofeedback system from laboratory testing through to clinical validation in the target setting, illustrating the importance of context when validating such systems. Each of the various components of the system were evaluated independently, and then in combination as the system is designed to be deployed. The results show a reduction in overall system accuracy between lab-based cross validation (>94%), testing on healthy participants (n = 10) in the target setting (>75%), through to test data collected from the clinical cohort (n = 11) (>59%). This study illustrates that the reliance on lab-based validation approaches may be misleading key stakeholders in the inertial sensor-based exercise biofeedback sector, makes recommendations for clinicians, developers and researchers, and discusses factors that may influence system performance at each stage of evaluation.
      14Scopus© Citations 5
  • Publication
    An Objective Methodology for the Selection of a Device for Continuous Mobility Assessment
    Continuous monitoring by wearable technology is ideal for quantifying mobility outcomes in “real-world” conditions. Concurrent factors such as validity, usability, and acceptability of such technology need to be accounted for when choosing a monitoring device. This study proposes a bespoke methodology focused on defining a decision matrix to allow for effective decision making. A weighting system based on responses (n = 69) from a purpose-built questionnaire circulated within the IMI Mobilise-D consortium and its external collaborators was established, accounting for respondents’ background and level of expertise in using wearables in clinical practice. Four domains (concurrent validity, CV; human factors, HF; wearability and usability, WU; and data capture process, CP), associated evaluation criteria, and scores were established through literature research and group discussions. While the CV was perceived as the most relevant domain (37%), the others were also considered highly relevant (WU: 30%, HF: 17%, CP: 16%). Respondents (~90%) preferred a hidden fixation and identified the lower back as an ideal sensor location for mobility outcomes. Overall, this study provides a novel, holistic, objective, as well as a standardized approach accounting for complementary aspects that should be considered by professionals and researchers when selecting a solution for continuous mobility monitoring.
      19Scopus© Citations 10
  • Publication
    Devising a Pace-Based Definition for “The Wall”: An Observational Analysis of Marathoners' Subjective Experiences of Fatigue
    Context Many runners report “hitting The Wall” (HTW) during a marathon (42.2 km). However, the performance manifestation of this subjectively experienced phenomenon remains unclear. Objective To identify a pace-based classification for HTW by integrating subjective reports of fatigue and runners' pacing profiles during a marathon. Design Cross-sectional study. Setting Public race event (2018 Dublin Marathon). Patients or Other Participants Eighty-three runners (28 [34%] women, 55 [66%] men, age = 41.5 ± 9.1 years, height = 1.73 ± 0.09 m, mass = 70.2 ± 10.1 kg). Main Outcome Measure(s) The pacing profiles for respondents to our postrace questionnaire that concerned the phenomenon of HTW were evaluated. Receiver operating characteristic analyses were performed on discretized outcomes of the time series of marathoners' paces during the race. Results Using the receiver operating characteristic analyses, we observed that runners could be classified as having experienced HTW if they ran any 1-km segment 11% slower than the average of the remaining segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.6) or if the standard deviation of the normalized 1-km split times exceeded 0.0532 (accuracy = 83%, sensitivity = 0.818, specificity = 0.8). Similarly, runners could be classified as having experienced HTW if they ran any 5-km segment 7.3% slower than the average of the remaining 5-km segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.644) or if the standard deviation of the normalized 5-km split times exceeded 0.0346 (accuracy = 82%, sensitivity = 0.909, specificity = 0.622). Conclusions These pace-based criteria could be valuable to researchers evaluating HTW prevalence in cohorts for whom they lack subjective questionnaire data.
      244Scopus© Citations 4
  • Publication
    A Thorough Examination of Morning Activity Patterns in Adults with Arthritis and Healthy Controls Using Actigraphy Data
    Background: Wearable sensors allow researchers to remotely capture digital health data, including physical activity, which may identify digital biomarkers to differentiate healthy and clinical cohorts. To date, research has focused on high-level data (e.g., overall step counts) which may limit our insights to whether people move differently, rather than how they move differently. Objective: This study therefore aimed to use actigraphy data to thoroughly examine activity patterns during the first hours following waking in arthritis patients (n = 45) and healthy controls (n = 30). Methods: Participants wore an Actigraph GT9X Link for 28 days. Activity counts were analysed and compared over varying epochs, ranging from 15 min to 4 h, starting with waking in the morning. The sum, and a measure of rate of change of cumulative activity in the period immediately after waking (area under the curve [AUC]) for each time period, was calculated for each participant, each day, and individual and group means were calculated. Two-tailed independent t tests determined differences between the groups. Results: No differences were seen for summed activity counts across any time period studied. However, differences were noted in the AUC analysis for the discrete measures of relative activity. Specifically, within the first 15, 30, 45, and 60 min following waking, the AUC for activity counts was significantly higher in arthritis patients compared to controls, particularly at the 30 min period (t = –4.24, p = 0.0002). Thus, while both cohorts moved the same amount, the way in which they moved was different. Conclusion: This study is the first to show that a detailed analysis of actigraphy variables could identify activity pattern changes associated with arthritis, where the high-level daily summaries did not. Results suggest discrete variables derived from raw data may be useful to help identify clinical cohorts and should be explored further to determine if they may be effective clinical biomarkers.
      38Scopus© Citations 6
  • Publication
    Comparing the Usability and Acceptability of Wearable Sensors Among Older Irish Adults in a Real-World Context: Observational Study
    Background: Wearable devices are valuable assessment tools for patient outcomes in contexts such as clinical trials. To besuccessfully deployed, however, participants must be willing to wear them. Another concern is that usability studies are rarelypublished, often fail to test devices beyond 24 hours, and need to be repeated frequently to ensure that contemporary devices areassessed.Objective: This study aimed to compare multiple wearable sensors in a real-world context to establish their usability within anolder adult (>50 years) population.Methods: Eight older adults wore seven devices for a minimum of 1 week each: Actigraph GT9x, Actibelt, Actiwatch, Biovotion,Hexoskin, Mc10 Biostamp_RC, and Wavelet. Usability was established through mixed methods using semistructured interviewsand three questionnaires, namely, the Intrinsic Motivation Inventory (IMI), the System Usability Scale (SUS), and an acceptabilityquestionnaire. Quantitative data were reported descriptively and qualitative data were analyzed using deductive content analysis.Data were then integrated using triangulation.Results: Results demonstrated that no device was considered optimal as all scored below average in the SUS (median, IQR;min-max=57.5, 12.5; 47.5-63.8). Hexoskin was the lowest scored device based on the IMI (3.6; 3.4-4.5), while Biovotion, Actibelt,and Mc10 Biostamp_RC achieved the highest median results on the acceptability questionnaire (3.6 on a 6-point Likert scale).Qualitatively, participants were willing to accept less comfort, less device discretion, and high charging burdens if the deviceswere perceived as useful, namely through the provision of feedback for the user. Participants agreed that the purpose of use is akey enabler for long-term compliance. These views were particularly noted by those not currently wearing an activity-trackingdevice. Participants believed that wrist-worn sensors were the most versatile and easy to use, and therefore, the most suitable forlong-term use. In particular, Actiwatch and Wavelet stood out for their comfort. The convergence of quantitative and qualitativedata was demonstrated in the study.Conclusions: Based on the results, the following context-specific recommendations can be made: (1) researchers should considertheir device selection in relation to both individual and environmental factors, and not simply the primary outcome of the researchstudy; (2) if researchers do not wish their participants to have access to feedback from the devices, then a simple, wrist-worndevice that acts as a watch is preferable; (3) if feedback is allowed, then it should be made available to help participants remainengaged; this is likely to apply only to people without cognitive impairments; (4) battery life of 1 week should be considered as a necessary featire to enhance data capture; (5) researchers should consider providing additional information about the purpose of devices to participants to support their continued use.
      429Scopus© Citations 52
  • Publication
    Feasibility cluster randomised controlled trial evaluating a theory-driven group-based complex intervention versus usual physiotherapy to support self-management of osteoarthritis and low back pain (SOLAS)
    Background: The self-management of osteoarthritis (OA) and low back pain (LBP) through activity and skills (SOLAS) theory-driven group-based complex intervention was developed primarily for the evaluation of its acceptability to patients and physiotherapists and the feasibility of trial procedures, to inform the potential for a definitive trial. Methods: This assessor-blinded multicentre two-arm parallel cluster randomised controlled feasibility trial compared the SOLAS intervention to usual individual physiotherapy (UP; pragmatic control group). Patients with OA of the hip, knee, lumbar spine and/or chronic LBP were recruited in primary care physiotherapy clinics (i.e. clusters) in Dublin, Ireland, between September 2014 and November 2015. The primary feasibility objectives were evaluated using quantitative methods and individual telephone interviews with purposive samples of participants and physiotherapists. A range of secondary outcomes were collected at baseline, 6 weeks (behaviour change only), 2 months and 6 months to explore the preliminary effects of the intervention. Analysis was by intention-to-treat according to participants' cluster allocation and involved descriptive analysis of the quantitative data and inductive thematic analysis of the qualitative interviews. A linear mixed model was used to contrast change over time in participant secondary outcomes between treatment arms, while adjusting for study waves and clusters. Results: Fourteen clusters were recruited (7 per trial arm), each cluster participated in two waves of recruitment, with the average cluster size below the target of six participants (intervention: mean (SD) = 4.92 (1.31), range 2-7; UP: mean (SD) = 5.08 (2.43), range 1-9). One hundred twenty participants (83.3% of n = 144 expected) were recruited (intervention n = 59; UP n = 61), with follow-up data obtained from 80.8% (n = 97) at 6 weeks, 84.2% (n = 101) at 2 months and 71.7% (n = 86) at 6 months. Most participants received treatment as allocated (intervention n = 49; UP n = 54). The qualitative interviews (12 participants; 10 physiotherapists (PTs) found the intervention and trial procedures acceptable and appropriate, with minimal feasible adaptations required. Linear mixed methods showed improvements in most secondary outcomes at 2 and 6 months with small between-group effects. Conclusions: While the SOLAS intervention and trial procedures were acceptable to participants and PTs, the recruitment of enough participants is the biggest obstacle to a definitive trial.
      104Scopus© Citations 7