Enhancement of sense of ownership using virtual and haptic feedback

Accomplishing motor function requires multimodal information, such as visual and haptic feedback, which induces a sense of ownership (SoO) over one’s own body part. In this study, we developed a visual–haptic human machine interface that combines three diferent types of feedback (visual, haptic, and kinesthetic) in the context of passive hand-grasping motion and aimed to generate SoO over a virtual hand. We tested two conditions, both conditions the three set of feedback were synchronous, the frst condition was in-phase, and the second condition was in antiphase. In both conditions, we utilized passive visual feedback (pre-recorded video of a real hand displayed), haptic feedback (balloon infated and defated), and kinesthetic feedback (fnger movement following the balloon curvature). To quantify the SoO, the participants’ reaction time was measured in response to a sense of threat. We found that most participants had a shorter reaction time under anti-phase condition, indicating that synchronous anti-phase of the multimodal system was better than in-phase condition for inducing a SoO of the virtual hand. We conclude that stronger haptic feedback has a key role in the SoO in accordance with visual information. Because the virtual hand is closing and the high pressure from the balloon against the hand creates the sensation of grasping and closing the hand, it appeared as though the person was closing his/her hand at the perceptual level

Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study

IntroductionIn a drip-and-ship model for endovascular thrombectomy (EVT), early identification of large vessel occlusion (LVO) and timely referral to a comprehensive center (CSC) are crucial when patients are admitted to an acute stroke center (ASC). Several artificial intelligence (AI) decision-aid tools are increasingly being used to facilitate the rapid identification of LVO. This retrospective cohort study aimed to evaluate the impact of deploying e-Stroke AI decision support software in the hyperacute stroke pathway on process metrics and patient outcomes at an ASC in the United Kingdom.MethodsExcept for the deployment of e-Stroke on 01 March 2020, there were no significant changes made to the stroke pathway at the ASC. The data were obtained from a prospective stroke registry between 01 January 2019 and 31 March 2021. The outcomes were compared between the 14 months before and 12 months after the deployment of AI (pre-e-Stroke cohort vs. post-e-Stroke cohort) on 01 March 2020. Time window analyses were performed using Welch’s t-test. Cochran–Mantel–Haenszel test was used to compare changes in disability at 3 months assessed by modified Rankin Score (mRS) ordinal shift analysis, and Fisher’s exact test was used for dichotomised mRS analysis.ResultsIn the pre-e-Stroke cohort, 19 of 22 patients referred received EVT. In the post-e-Stroke cohort, 21 of the 25 patients referred were treated. The mean door-in-door-out (DIDO) and door-to-referral times in pre-e-Stroke vs. post-e-Stroke cohorts were 141 vs. 79 min (difference 62 min, 95% CI 96.9–26.8 min, p < 0.001) and 71 vs. 44 min (difference 27 min, 95% CI 47.4–5.4 min, p = 0.01), respectively. The adjusted odds ratio (age and NIHSS) for mRS ordinal shift analysis at 3 months was 3.14 (95% CI 0.99–10.51, p = 0.06) and the dichotomized mRS 0–2 at 3 months was 16% vs. 48% (p = 0.04) in the pre- vs. post-e-Stroke cohorts, respectively.ConclusionIn this single-center study in the United Kingdom, the DIDO time significantly decreased since the introduction of e-Stroke decision support software into an ASC hyperacute stroke pathway. The reduction in door-in to referral time indicates faster image interpretation and referral for EVT. There was an indication of an increased proportion of patients regaining independent function after EVT. However, this should be interpreted with caution given the small sample size. Larger, prospective studies and further systematic real-world evaluation are needed to demonstrate the widespread generalisability of these findings

A multidimensional approach to older patients during COVID-19 pandemic: a position paper of the Special Interest Group on Comprehensive Geriatric Assessment of the European Geriatric Medicine Society (EuGMS)

Purpose: The COVID-19 pandemic has been a dramatic trigger that has challenged the intrinsic capacity of older adults and of society. Due to the consequences for the older population worldwide, the Special Interest Group on Comprehensive Geriatric Assessment (CGA) of the European Geriatric Medicine Society (EuGMS) took the initiative of collecting evidence on the usefulness of the CGA-based multidimensional approach to older people during the COVID-19 pandemic. Methods: A narrative review of the most relevant articles published between January 2020 and November 2022 that focused on the multidimensional assessment of older adults during the COVID-19 pandemic. Results: Current evidence supports the critical role of the multidimensional approach to identify older adults hospitalized with COVID-19 at higher risk of longer hospitalization, functional decline, and short-term mortality. This approach appears to also be pivotal for the adequate stratification and management of the post-COVID condition as well as for the adoption of preventive measures (e.g., vaccinations, healthy lifestyle) among non-infected individuals. Conclusion: Collecting information on multiple health domains (e.g., functional, cognitive, nutritional, social status, mobility, comorbidities, and polypharmacy) provides a better understanding of the intrinsic capacities and resilience of older adults affected by SARS-CoV-2 infection. The EuGMS SIG on CGA endorses the adoption of the multidimensional approach to guide the clinical management of older adults during the COVID-19 pandemic

Comprehensive geriatric assessment in older people : an umbrella review of health outcomes

Background: Comprehensive geriatric assessment (CGA) has been in use for the last three decades. However, some doubts remain regarding its clinical use. Therefore, we aimed to capture the breadth of outcomes reported and assess the strength of evidence of the use of comprehensive geriatric assessment (CGA) for health outcomes in older Methods: Umbrella review of systematic reviews of the use of CGA in older adults searching in Pubmed, Embase, Scopus, Cochrane library and CINHAL until 05 November 2021. All possible health outcomes were eligible. Two independent reviewers extracted key data. The grading of evidence was carried out using the GRADE for intervention studies, whilst data regarding systematic reviews were reported as narrative findings. Results: Among 1,683 papers, 31 systematic reviews (19 with meta-analysis) were considered, including 279,744 subjects. Overall, 13/53 outcomes were statistically significant (P < 0.05). There was high certainty of evidence that CGA reduces nursing home admission (risk ratio [RR] = 0.86; 95% confidence interval [CI]: 0.75–0.89), risk of falls (RR = 0.51; 95%CI: 0.29–0.89), and pressure sores (RR = 0.46; 95%CI: 0.24–0.89) in hospital medical setting; decreases the risk of delirium (OR = 0.71; 95%CI: 0.54–0.92) in hip fracture; decreases the risk of physical frailty in community-dwelling older adults (RR = 0.77; 95%CI: 0.64–0.93). Systematic reviews without meta-analysis indicate that CGA improves clinical outcomes in oncology, haematology, and in emergency department. Conclusions: CGA seems to be beneficial in the hospital medical setting for multiple health outcomes, with a high certainty of evidence. The evidence of benefits is less strong for the use of CGA in other settings