Information and communication technology solutions for outdoor navigation in dementia

INTRODUCTION: Information and communication technology (ICT) is potentially mature enough to empower outdoor and social activities in dementia. However, actual ICT-based devices have limited functionality and impact, mainly limited to safety. What is an ideal operational framework to enhance this field to support outdoor and social activities? METHODS: Review of literature and cross-disciplinary expert discussion. RESULTS: A situation-aware ICT requires a flexible fine-tuning by stakeholders of system usability and complexity of function, and of user safety and autonomy. It should operate by artificial intelligence/machine learning and should reflect harmonized stakeholder values, social context, and user residual cognitive functions. ICT services should be proposed at the prodromal stage of dementia and should be carefully validated within the life space of users in terms of quality of life, social activities, and costs. DISCUSSION: The operational framework has the potential to produce ICT and services with high clinical impact but requires substantial investment

Focal Spot, Fall/Winter 1989

https://digitalcommons.wustl.edu/focal_spot_archives/1053/thumbnail.jp

Focal Spot, Fall/Winter 1992

https://digitalcommons.wustl.edu/focal_spot_archives/1062/thumbnail.jp

Additively manufactured versus conventionally pressed cranioplasty implants: An accuracy comparison

This article compared the accuracy of producing patient-specific cranioplasty implants using four different approaches. Benchmark geometry was designed to represent a cranium and a defect added simulating a craniectomy. An ‘ideal’ contour reconstruction was calculated and compared against reconstructions resulting from the four approaches –‘conventional’, ‘semi-digital’, ‘digital – non-automated’ and ‘digital – semi-automated’. The ‘conventional’ approach relied on hand carving a reconstruction, turning this into a press tool, and pressing titanium sheet. This approach is common in the UK National Health Service. The ‘semi-digital’ approach removed the hand-carving element. Both of the ‘digital’ approaches utilised additive manufacturing to produce the end-use implant. The geometries were designed using a non-specialised computer-aided design software and a semi-automated cranioplasty implant-specific computer-aided design software. It was found that all plates were clinically acceptable and that the digitally designed and additive manufacturing plates were as accurate as the conventional implants. There were no significant differences between the additive manufacturing plates designed using non-specialised computer-aided design software and those designed using the semi-automated tool. The semi-automated software and additive manufacturing production process were capable of producing cranioplasty implants of similar accuracy to multi-purpose software and additive manufacturing, and both were more accurate than handmade implants. The difference was not of clinical significance, demonstrating that the accuracy of additive manufacturing cranioplasty implants meets current best practice

Healthy You

https://scholarlyworks.lvhn.org/healthy-you/1037/thumbnail.jp

Venous air embolisms and sitting position in Helsinki pineal region surgery

Peer reviewe

Outlook Magazine, Spring 2014

https://digitalcommons.wustl.edu/outlook/1192/thumbnail.jp

Risk-Based Path Planning for a Steerable Flexible Probe for Neurosurgical Intervention

presentazione Poste

Risk Factors for Perioperative Brain Lesions in Infants With Congenital Heart Disease: A European Collaboration

Background: Infants with congenital heart disease are at risk of brain injury and impaired neurodevelopment. The aim was to investigate risk factors for perioperative brain lesions in infants with congenital heart disease. Methods: Infants with transposition of the great arteries, single ventricle physiology, and left ventricular outflow tract and/or aortic arch obstruction undergoing cardiac surgery <6 weeks after birth from 3 European cohorts (Utrecht, Zurich, and London) were combined. Brain lesions were scored on preoperative (transposition of the great arteries N=104; single ventricle physiology N=35; and left ventricular outflow tract and/or aortic arch obstruction N=41) and postoperative (transposition of the great arteries N=88; single ventricle physiology N=28; and left ventricular outflow tract and/or aortic arch obstruction N=30) magnetic resonance imaging for risk factor analysis of arterial ischemic stroke, cerebral sinus venous thrombosis, and white matter injury. Results: Preoperatively, induced vaginal delivery (odds ratio [OR], 2.23 [95% CI, 1.06-4.70]) was associated with white matter injury and balloon atrial septostomy increased the risk of white matter injury (OR, 2.51 [95% CI, 1.23-5.20]) and arterial ischemic stroke (OR, 4.49 [95% CI, 1.20-21.49]). Postoperatively, younger postnatal age at surgery (OR, 1.18 [95% CI, 1.05-1.33]) and selective cerebral perfusion, particularly at ≤20 °C (OR, 13.46 [95% CI, 3.58-67.10]), were associated with new arterial ischemic stroke. Single ventricle physiology was associated with new white matter injury (OR, 2.88 [95% CI, 1.20-6.95]) and transposition of the great arteries with new cerebral sinus venous thrombosis (OR, 13.47 [95% CI, 2.28-95.66]). Delayed sternal closure (OR, 3.47 [95% CI, 1.08-13.06]) and lower intraoperative temperatures (OR, 1.22 [95% CI, 1.07-1.36]) also increased the risk of new cerebral sinus venous thrombosis. Conclusions: Delivery planning and surgery timing may be modifiable risk factors that allow personalized treatment to minimize the risk of perioperative brain injury in severe congenital heart disease. Further research is needed to optimize cerebral perfusion techniques for neonatal surgery and to confirm the relationship between cerebral sinus venous thrombosis and perioperative risk factors. Keywords: heart diseases; ischemic stroke; magnetic resonance imaging; pedatrics; risk factors; venous thrombosis; white matter

Data-Driven Operational and Safety Analysis of Emerging Shared Electric Scooter Systems

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters. Perceiving the growth of such a micro-mobility mode, this study aimed to investigate E-Scooter operations and safety by collecting, processing, and mining various unconventional data sources. First, origin-destination (OD) data were collected for E-Scooters to analyze how E-Scooters have been used in urban areas. The key factors that drive users to choose E-Scooters over other options (i.e., shared bikes and taxis) were identified. Concerning user safety tied to the growing usage, we further assessed E-Scooter user guidelines in urban areas in the U.S. Scoring models have been developed for evaluating the adopted guidelines. It was found that the areas with E-Scooter systems have notable disparities in terms of the safety factors considered in the guidelines. Built upon the usage and policy analyses, this study also creatively collected news reports as an alternative data source for E-Scooter safety analysis. Three-year news reports were collected for E-Scooter-involved crashes in the U.S. The identified reports are typical crash events with great media impact. Many detailed variables such as location, time, riders’ information, and crash type were mined. This offers a lens to highlight the macro-level crash issues confronted with E-Scooters. Besides the macro-level safety analysis, we also conducted micro-level analysis of E-Scooter riding risk. An all-in-one mobile sensing system has been developed using the Raspberry Pi platform with multiple sensors including GPS, LiDAR, and motion trackers. Naturalistic riding data such as vibration, speed, and location were collected simultaneously when riding E-Scooters. Such mobile sensing technologies have been shown as an innovative way to help gather valuable data for quantifying riding risk. A demonstration on expanding the mobile sensing technologies was conducted to analyze the impact of wheel size and riding infrastructure on E-Scooter riding experience. The quantitative analysis framework proposed in this study can be further extended for evaluating the quality of road infrastructure, which will be helpful for understanding the readiness of infrastructure for supporting the safe use of micro-mobility systems. To sum up, this study contributes to the literature in several distinct ways. First, it has developed mode choice models for revealing the use of E-Scooters among other existing competitive modes for connecting urban metro systems. Second, it has systematically assessed existing E-Scooter user guidelines in the U.S. Moreover, it demonstrated the use of surrogate data sources (e.g., news reports) to assist safety studies in cases where there is no available crash data. Last but not least, it developed the mobile sensing system and evaluation framework for enabling naturalistic riding data collection and risk assessment, which helps evaluate riding behavior and infrastructure performance for supporting micro-mobility systems