To determine what type (e.g., television, photographs, music, etc), content (e.g., nature scenes, family members, etc), and duration of visual and auditory stimuli should be provided to intensive care unit patients during their hospitalisation. This mixed-methods study followed an exploratory-descriptive design. In total, 31 participants were interviewed: 19 were former critically ill patients in the intensive care unit and 12 were nursing experts, all from a university hospital in Switzerland. Based on current practice, patients and nurses were familiar with receiving and providing television, photographs, radio, and musical stimuli, with no specific exposure to virtual reality, aside from that in their personal lives. Data were collected from the former patients using structured interviews, whereas semi-structured interviews were used for the nursing experts. Overall, patient and expert opinions aligned well; both groups agreed that receiving visual and/or auditory stimuli would benefit patients. Photographs, television, and virtual reality were the visual stimuli most chosen by the patients, with an emphasis on nature-focused content. When appropriate, audio matching the content should be provided alongside the visual stimuli to act as a distraction from the hospital environment. Visual stimuli should not exceed 10-15 min, while auditory stimuli should not exceed one hour. Sensory overload and deprivation are common problems in the intensive care unit with negative effects on patient outcomes. Based on patient and expert opinions, visual and auditory stimuli are desired by patients and could help address these issues.

Purpose: The noise levels in intensive care units have been repeatedly reported to exceed the recommended guidelines and yield negative health outcomes among healthcare professionals. However, it is unclear which sound sources within this environment are perceived as disturbing. Therefore, this study aimed to evaluate how healthcare professionals in Germany, Switzerland, and Austria perceive the sound levels and the associated sound sources within their work environment and explore sound reduction strategies. Material and methods: An online survey was conducted among 350 healthcare professionals working in intensive care units. The survey consisted of items on demographic and hospital data and questions about the perception of the sound levels [1 (strongly disagree) to 5 (strongly agree)], disturbance from sound sources [1 (not disturbing at all) to 5 (very disturbing)], and implementation potential, feasibility, and motivation to reduce sound reduction measures [1 (not high at all) to 5 (very high)]. Results: Approximately 69.3% of the healthcare professionals perceived the sound levels in the ICUs as too high. Short-lasting human sounds (e.g. moans or laughs) [mean (M) ± standard deviation (SD) = 3.30 ± 0.81], devices and alarms (M ± SD = 2.67 ± 0.59), and short-lasting object sounds (M ± SD = 2.55 ± 0.68) were perceived as the most disturbing sounds. Reducing medical equipment alarms was considered to have greater implementation potential [M ± SD = 3.62 ± 0.92, t(334) = -7.30, p < 0.001], feasibility [M ± SD = 3.19 ± 0.93, t(334) = -11.02, p < 0.001], and motivation [M ± SD = 3.85 ± 0.89, t(334) = -10.10, p < 0.001] for reducing the sound levels. Conclusion: This study showed that healthcare professionals perceive short-lasting human sounds as most disturbing and rated reducing medical equipment alarms as the best approach to reduce the sound levels in terms of potential, feasibility, and motivation for implementation.

The use of virtual reality (VR) stimulation in clinical settings has increased in recent years. In particular, there has been increasing interest in the use of VR stimulation for a variety of purposes, including medical training, pain therapy, and relaxation. Unfortunately, there is still a limited amount of real-world 360-degree content that is both available and suitable for these applications. Therefore, this tutorial paper describes a pipeline for the creation of custom VR content. It covers the planning and designing of content; the selection of appropriate equipment; the creation and processing of footage; and the deployment, visualization, and evaluation of the VR experience. This paper aims to provide a set of guidelines, based on first-hand experience, that readers can use to help create their own 360-degree videos. By discussing and elaborating upon the challenges associated with making 360-degree content, this tutorial can help researchers and health care professionals anticipate and avoid common pitfalls during their own content creation process.

Background: Digital sensing devices have become an increasingly important component of modern biomedical research, as they help provide objective insights into individuals’ everyday behavior in terms of changes in motor and nonmotor symptoms. However, there are significant barriers to the adoption of sensor-enhanced biomedical solutions in terms of both technical expertise and associated costs. The currently available solutions neither allow easy integration of custom sensing devices nor offer a practicable methodology in cases of limited resources. This has become particularly relevant, given the need for real-time sensor data that could help lower health care costs by reducing the frequency of clinical assessments performed by specialists and improve access to health assessments (eg, for people living in remote areas or older adults living at home). Objective: The objective of this paper is to detail the end-to-end development of a novel sensor recording software system that supports the integration of heterogeneous sensor technologies, runs as an on-demand service on consumer-grade hardware to build sensor systems, and can be easily used to reliably record longitudinal sensor measurements in research settings. Methods: The proposed software system is based on a server-client architecture, consisting of multiple self-contained microservices that communicated with each other (eg, the web server transfers data to a database instance) and were implemented as Docker containers. The design of the software is based on state-of-the-art open-source technologies (eg, Node.js or MongoDB), which fulfill nonfunctional requirements and reduce associated costs. A series of programs to facilitate the use of the software were documented. To demonstrate performance, the software was tested in 3 studies (2 gait studies and 1 behavioral study assessing activities of daily living) that ran between 2 and 225 days, with a total of 114 participants. We used descriptive statistics to evaluate longitudinal measurements for reliability, error rates, throughput rates, latency, and usability (with the System Usability Scale [SUS] and the Post-Study System Usability Questionnaire [PSSUQ]). Results: Three qualitative features (event annotation program, sample delay analysis program, and monitoring dashboard) were elaborated and realized as integrated programs. Our quantitative findings demonstrate that the system operates reliably on consumer-grade hardware, even across multiple months (>420 days), providing high throughput (2000 requests per second) with a low latency and error rate (<0.002%). In addition, the results of the usability tests indicate that the system is effective, efficient, and satisfactory to use (mean usability ratings for the SUS and PSSUQ were 89.5 and 1.62, respectively). Conclusions: Overall, this sensor recording software could be leveraged to test sensor devices, as well as to develop and validate algorithms that are able to extract digital measures (eg, gait parameters or actigraphy). The proposed software could help significantly reduce barriers related to sensor-enhanced biomedical research and allow researchers to focus on the research questions at hand rather than on developing recording technologies.

Background: Gait impairments are common in stroke survivors, negatively impacting their overall quality of life. Therefore, gait rehabilitation is often targeted during in-clinic rehabilitation. While standardized assessments are available for inpatient evaluation, the literature often reports variable results when these assessments are conducted in a home environment. Several factors, such as the presence of an observer, the environment itself, or the technology used, may contribute to these differing results. Therefore, it is relevant to establish unsupervised capacity assessments for both in-clinic use and across the continuum of care. Objective: This study aimed to investigate the effect of supervision on the outcomes of a sensor-based 10-meter walk test conducted in a clinical setting, maintaining a controlled environment and setup. Methods: In total, 21 stroke survivors (10 female, 11 male; age: mean 63.9, SD 15.5 years) were assigned alternately to one of two data collection sequences and tested over 4 consecutive days, alternating between supervised test (ST) and unsupervised test (UST) assessments. For both assessments, participants were required to walk a set distance of 10 meters as fast as possible while data were collected using a single wearable sensor (Physilog 5) attached to each shoe. After each walking assessment, the participants completed the Intrinsic Motivation Inventory. Statistical analyses were conducted to examine the mean speed, stride length, and cadence, across repeated measurements and between assessment conditions. Results: The intraclass correlation coefficient indicated good to excellent reliability for speed (ST: κ=0.93, P<.001; UST: κ=0.93, P<.001), stride length (ST: κ=0.92, P<.001; UST: κ=0.88, P<.001), and cadence (ST: κ=0.91, P<.001; UST: κ=0.95, P<.001) across repeated measurements for both ST and UST assessments. There was no significant effect of testing order (ie, sequence A vs B). Comparing ST and UST, there were no significant differences in speed (t39=–0.735, P=.47, 95% CI 0.06-0.03), stride length (z=0.835, P=.80), or cadence (t39=–0.501, P=.62, 95% CI 3.38-2.04) between the 2 assessments. The overall motivation did not show any significant differences between the ST and UST conditions (P>.05). However, the self-reported perceived competence increased during the unsupervised assessment from the first to the second measurement. Conclusions: Unsupervised gait capacity assessments offer a reliable alternative to supervised assessments in a clinical environment, showing comparable results for gait speed, stride length, and cadence, with no differences in overall motivation between the two. Future work should build upon these findings to extend unsupervised assessment of both capacity and performance in home environments. Such assessments could allow improved and more specific tracking of rehabilitation progress across the continuum of care.

For patients suffering from neurodegenerative disorders, the behavior and activities of daily living are an indicator of a change in health status, and home-monitoring over a prolonged period of time by unobtrusive sensors is a promising technology to foster independent living and maintain quality of life. The aim of this pilot case study was the development of a multi-sensor system in an apartment to unobtrusively monitor patients at home during the day and night. The developed system is based on unobtrusive sensors using basic technologies and gold-standard medical devices measuring physiological (e.g., mobile electrocardiogram), movement (e.g., motion tracking system), and environmental parameters (e.g., temperature). The system was evaluated during one session by a healthy 32-year-old male, and results showed that the sensor system measured accurately during the participant’s stay. Furthermore, the participant did not report any negative experiences. Overall, the multi-sensor system has great potential to bridge the gap between laboratories and older adults’ homes and thus for a deep and novel understanding of human behavioral and neurological disorders. Finally, this new understanding could be utilized to develop new algorithms and sensor systems to address problems and increase the quality of life of our aging society and patients with neurological disorders.