Dataset Information

Eye Tracking Supported Human Factors Testing Improving Patient Training.

ABSTRACT: The handling of left ventricular assist devices (LVADs) can be challenging for patients and requires appropriate training. The devices' usability impacts patients' safety and quality of life. In this study, an eye tracking supported human factors testing was performed to reveal problems during use and test the trainings' effectiveness. In total 32 HeartWare HVAD patients (including 6 pre-VAD patients) and 3 technical experts as control group performed a battery change (BC) and a controller change (CC) as an everyday and emergency scenario on a training device. By tracking the patients' gaze point, task duration and pump-off time were evaluated. Patients with LVAD support ≥1 year showed significantly shorter BC task duration than patients with LVAD support <1 year (p = 0.008). In contrast their CC task duration (p = 0.002) and pump-off times (median = 12.35 s) were higher than for LVAD support patients <1 year (median = 5.3 s) with p = 0.001. The shorter BC task duration for patients with LVAD support ≥1 year indicate that with time patients establish routines and gain confidence using their device. The opposite effect was found for CC task duration and pump-off times. This implies the need for intermittent re-training of less frequent tasks to increase patients' safety.

SUBMITTER: Weiss KE

PROVIDER: S-EPMC7994237 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Eye Tracking Supported Human Factors Testing Improving Patient Training.

Weiss Kerrin Elisabeth KE Hoermandinger Christoph C Mueller Marcus M Schmid Daners Marianne M Potapov Evgenij V EV Falk Volkmar V Meboldt Mirko M Lohmeyer Quentin Q

Journal of medical systems 20210325 5

The handling of left ventricular assist devices (LVADs) can be challenging for patients and requires appropriate training. The devices' usability impacts patients' safety and quality of life. In this study, an eye tracking supported human factors testing was performed to reveal problems during use and test the trainings' effectiveness. In total 32 HeartWare HVAD patients (including 6 pre-VAD patients) and 3 technical experts as control group performed a battery change (BC) and a controller chang ...[more]

PMID: 33768346

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Project description:BackgroundDespite recent design improvements, human factors issues continue to challenge left ventricular assist device (LVAD) therapy. The aim of this study was to evaluate user experience of former non-HeartMate 3 (HM3) LVAD patients post heart transplantation (HTX) and laypersons (LP) with HM3 LVAD peripherals in simulated everyday and emergency scenarios.MethodsThis single center cohort study included untrained HTX and LP. Seven scenarios, including battery exchanges (without alarm, advisory alarm, dim light, consolidated bag), change of power supply, driveline dis-/reconnection and controller exchange were simulated. Subjects' gaze behavior was recorded using eye tracking technology. Success rate, pump-off-time, duration to success (DTS), percental fixation duration per areas of interest and post-scenario-survey results were defined as outcome measures.ResultsThirty subjects completed 210 scenarios, initially solving 82.4% (HTX vs. LP, p = 1.00). Changing power supply revealed highest complexity (DTS = 251 ± 93s, p = 0.76): 26.7% succeeded at first attempt (p = 0.68), 56.7% at second attempt, with significantly more LP failing (p = 0.04), resulting in 10 hazards from driveline disconnections (pump-off-time 2-118s, p = 0.25). Comparison on initial success showed differences in fixation durations for seven areas of interest (p < 0.037). Decreasing DTS during battery exchanges (p < 0.001) indicate high learnability. Exchanging batteries within the bag took longer (median DTS = 75.0 (IQR = 45.0)s, p = 0.09), especially in elderly subjects (r = 0.61, p < 0.001). Subjects with less initial success were more afraid of making mistakes (p = 0.048).ConclusionThis eye tracking based human factors study provided insights into user experiences in handling HM3 peripherals. It highlights unintuitive and hazardous characteristics, providing guidance for future user-centered design of LVAD wearables.

Project description:BackgroundTreadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a third agent to the traditional one-to-one physiotherapist-patient (Pht-Pt) relationship, the therapist might not be fully aware of the patient's motor performance. This gap has been bridged by the integration in rehabilitation robots of a visual FeedBack (FB) that informs about patient's performance. Despite the recognized importance of FB in t-RAGT, the optimal role of the therapist in the complex patient-robot interaction is still unclear. This study aimed to describe whether the type of FB combined with different modalities of Pht's interaction toward Pt would affect the patients' visual attention and emotional engagement during t-RAGT.MethodsTen individuals with incomplete Spinal Cord Injury (C or D ASIA Impairment Scale level) were assessed using eye-tracking (ET) and high-density EEG during seven t-RAGT sessions with Lokomat where (i) three types of visual FB (chart, emoticon and game) and (ii) three levels of Pht-Pt interaction (low, medium and high) were randomly combined. ET metrics (fixations and saccades) were extracted for each of the three defined areas of interest (AoI) (monitor, Pht and surrounding) and compared among the different experimental conditions (FB, Pht-Pt interaction level). The EEG spectral activations in theta and alpha bands were reconstructed for each FB type applying Welch periodogram to data localised in the whole grey matter volume using sLORETA.ResultsWe found an effect of FB type factor on all the ET metrics computed in the three AoIs while the factor Pht-Pt interaction level also combined with FB type showed an effect only on the ET metrics calculated in Pht and surrounding AoIs. Neural activation in brain regions crucial for social cognition resulted for high Pht-Pt interaction level, while activation of the insula was found during low interaction, independently on the FB used.ConclusionsThe type of FB and the way in which Pht supports the patients both have a strong impact on patients' engagement and should be considered in the design of a t-RAGT-based rehabilitation session.

Project description:ObjectivesEye-tracking technology has emerged as a potentially useful learner assessment tool in several medical specialties. In the fields of general surgery and anesthesiology, it has been shown to reliably differentiate between different levels of expertise in procedural skills. In the field of radiology, it has been shown to be a valid assessment tool for diagnostic test interpretation. Current methods of competency assessment in point-of-care ultrasound (POCUS) remain a challenge, because they require significant direct observation time by an instructor. The purpose of this study was to determine if eye-tracking technology can accurately distinguish between novice and experts in the interpretation of POCUS clips, specifically of the focused assessment using sonography in trauma (FAST) scan.MethodsA convenience sample of medical students, residents, and emergency physicians from a single academic emergency department were invited to participate. Participants included both novices and experts in POCUS. Each participant completed a baseline questionnaire and viewed 16 video clips of a FAST ultrasound examination while their gaze patterns were recorded by a commercially available eye-tracking device. The primary outcome was total gaze time on the area of interest (AOI). Secondary outcomes included total time to fixation, mean number of fixations, and mean duration of first fixation on the AOI.ResultsFifteen novices and 15 experts completed this study. For total gaze time on the AOI, experts fixated their gaze significantly longer than novices (75.8 ± 16.2 seconds vs. 56.6 ± 12.8 seconds, p = 0.001). Similarly, experts were significantly faster to fixate on the AOI and had a higher fixation count on the AOI (8.5 ± 4.0 seconds vs. 15.1 ± 6.8 seconds, p = 0.003; and 170 ± 30 vs. 143 ± 28 seconds, p = 0.016). There were no differences on the mean duration of first fixation on the AOI (0.42 ± 0.12 seconds vs. 0.39 ± 0.09 seconds, p = 0.467).ConclusionEye-tracking technology shows the potential to differentiate between experts and novices by their gaze patterns on video clips of FAST examinations. The total gaze time on the AOI may be a useful metric to help in the assessment of competency in POCUS image interpretation. In addition, the evaluation of gaze patterns may help educators identify causes of interpretation errors. Future studies are needed to further validate these metrics in a larger cohort.

Dataset Information

Eye Tracking Supported Human Factors Testing Improving Patient Training.

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Eye Tracking Supported Human Factors Testing Improving Patient Training.

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