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Introduction
Stroke is the leading neurological cause of adult long-term disability in Europe. Even though functional consequences directly related to neurological impairment are well studied, post-stroke trajectories of functional health according to the International Classification of Functioning, Disability and Health are poorly understood. Particularly, no study investigated the relationship between post-stroke trajectories of activities of daily living (ADL) and self-rated health (SRH). However, such knowledge is of major importance to identify patients at risk of unfavourable courses. This prospective observational study aims to investigate trajectories of ADL and SRH, and their modifying factors in the course of the first year after stroke.
Methods and analysis
The study will consecutively enrol 300 patients admitted to a tertiary care hospital with acute ischaemic stroke or transient ischaemic attack (TIA; Age, Blood Pressure, Clinical Features, Duration of symptoms, Diabetes score ≥3). Patient inclusion is planned from May 2021 to September 2022. All participants will complete an interview assessing ADL, SRH, mental health, views on ageing and resilience-related concepts. Participants will be interviewed face-to-face 1–5 days post-stroke/TIA in the hospital; and will be followed up after 6 weeks, 3 months, 6 months and 12 months via telephone. The 12-month follow-up will also include a neurological assessment. Primary endpoints are ADL operationalised by modified Rankin Scale scores and SRH. Secondary outcomes are further measures of ADL, functional health, physical activity, falls and fatigue. Views on ageing, social support, resilience-related concepts, affect, frailty, illness perceptions and loneliness will be examined as modifying factors. Analyses will investigate the bidirectional relationship between SRH and ADL using bivariate latent change score models.
Ethics and dissemination
The study has been approved by the institutional review board of the University Medicine Greifswald (Ref. BB 237/20). The results will be disseminated through scientific publications, conferences and media. Moreover, study results and potential implications will be discussed with patient representatives.
Trial registration number NCT04704635.
Background
Numerous wearables are used in a research context to record cardiac activity although their validity and usability has not been fully investigated. The objectives of this study is the cross-model comparison of data quality at different realistic use cases (cognitive and physical tasks). The recording quality is expressed by the ability to accurately detect the QRS complex, the amount of noise in the data, and the quality of RR intervals.
Methods
Five ECG devices (eMotion Faros 360°, Hexoskin Hx1, NeXus-10 MKII, Polar RS800 Multi and SOMNOtouch NIBP) were attached and simultaneously tested in 13 participants. Used test conditions included: measurements during rest, treadmill walking/running, and a cognitive 2-back task. Signal quality was assessed by a new local morphological quality parameter morphSQ which is defined as a weighted peak noise-to-signal ratio on percentage scale. The QRS detection performance was evaluated with eplimited on synchronized data by comparison to ground truth annotations. A modification of the Smith-Waterman algorithm has been used to assess the RR interval quality and to classify incorrect beat annotations. Evaluation metrics includes the positive predictive value, false negative rates, and F1 scores for beat detection performance.
Results
All used devices achieved sufficient signal quality in non-movement conditions. Over all experimental phases, insufficient quality expressed by morphSQ values below 10% was only found in 1.22% of the recorded beats using eMotion Faros 360°whereas the rate was 8.67% with Hexoskin Hx1. Nevertheless, QRS detection performed well across all used devices with positive predictive values between 0.985 and 1.000. False negative rates are ranging between 0.003 and 0.017. eMotion Faros 360°achieved the most stable results among the tested devices with only 5 false positive and 19 misplaced beats across all recordings identified by the Smith-Waterman approach.
Conclusion
Data quality was assessed by two new approaches: analyzing the noise-to-signal ratio using morphSQ, and RR interval quality using Smith-Waterman. Both methods deliver comparable results. However the Smith-Waterman approach allows the direct comparison of RR intervals without the need for signal synchronization whereas morphSQ can be computed locally.
Measuring mental workload at the workplace using (psycho-) physiological measurement techniques seems desirable but is difficult to implement. Conventional analysis techniques are designed to cover longer measurement durations, neglecting the demands of modern work places: high worker flexibility and constantly fluctuating mental workload. As an alternative analysis approach, measurement (resp. analysis) duration can be shortened and event-based pattern analysis of various physiological parameters can be performed. The effects of such approaches are demonstrated by experimental examples. Furthermore, an event-timestamp independent framework is presented. Focusing on occasionally occurring peaks and longer lasting plateaus in mental workload trajectories, an automatized analysis of workload during work processes becomes possible.
Practical relevance: With steadily increasing cognitive demands at work the risk of mental fatigue increases too. Mental workload is not directly observable at the workplace and the objective measurement and interpretation is complicated. Improving the overall assessment and analysis strategies for (physiological) mental workload indicators can benefit the quality of risk assessments of workplaces and processes as well as enable the possibility of demand-orientated control of (informational) assistance systems to prevent mental overload and resulting health constraints.