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 different 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 first 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 inflated and deflated), and kinesthetic feedback (finger 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.

Introduction: In 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. Methods: Except 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. Results: In 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. Conclusion: In 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.

Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19.

Acute stroke care demands real-time, specialist-led treatment decisions, including thrombolysis and referral for mechanical thrombectomy. Pathways designed to deliver time-critical interventions for stroke patients are under intense pressure due to the impact of COVID-19 pandemic. In response to this unprecedented burden on acute care services, stroke clinicians are having to reconfigure existing clinical pathways both within and between hospitals. Incorporating artificial intelligence and digital communication support into clinical pathways offers an opportunity to mitigate the disruption to acute stroke care. In this case study we describe how Royal Berkshire Hospital, working collaboratively with Brainomix, a UK-based artificial intelligence software company, adopted technological innovation and integrated it into the hyperacute stroke pathway. A case is presented to demonstrate how this innovation can support patient care and deliver successful patient outcomes. We believe this model can be adopted in other hospitals and networks to deliver safe and efficient hyperacute stroke care.

Proportion of acute ischaemic strokes attributable to a cardiac aetiology in an unselected young patient population: A single centre experience.

The incidence of acute ischaemic stroke in young patients is increasing and identifying the underlying cause is critically important with regards to their optimal management. The true proportion of cardiac causes of stroke in young patients is poorly defined. We aimed to determine the proportion of strokes attributable to cardiac causes in an unselected, consecutive cohort of young patients. We used the database of a large stroke service to identify patients aged ≤55 years presenting with stroke between 01 January 2015 and 31 December 2017. We reviewed their clinical notes and investigations and then categorised patients by the cause of their stroke.We screened 202 cases, and excluded 35, resulting in a study population of 167 patients; 24.0% (40/167) had a cardiac cause of stroke including 9.6% (16/167) had patent foramen ovale, 9.0% (15/167) had intracardiac source of embolus and 5.4% (9/167) had atrial fibrillation; 50.8% (85/167) had other more likely causes; and 25.1% (42/167) had no clear underlying cause.A high proportion (24%) of strokes in young patients are secondary to a cardiac cause. Thorough investigation in these patients is warranted and requires close interdisciplinary links between cardiologists and stroke physicians to ensure optimal management.

Headache in a young male: the clot thickens.

Cerebral venous sinus thrombosis  is a rare but serious cause of headache. In this report, we present a young man with poorly controlled Crohn's disease who presented with a 2-week history of headache and fluctuating left-sided sensory and motor symptoms. CT demonstrated changes consistent with either a subarachnoid haemorrhage or venous sinus thrombosis. The ensuing magnetic resonance venogram confirmed superior sagittal venous sinus thrombosis and an infarct of his right superior frontal lobe. The patient was started on low-molecular weight heparin and steroids. He required multi-disciplinary input from the stroke physicians, neurologists, gastroenterologists, dieticians and physiotherapists. He made a full neurological recovery and is now on long-term azathioprine. The purpose of this report is to highlight the consideration of venous sinus thrombosis in the diagnosis of headache and as a rare extraintestinal complication of Crohn's disease.