Background and Purpose —This study describes the methodology, patient outcome, and use of hospital and rehabilitation services at 3 months of a population-based randomized controlled trial. The purpose was to evaluate rehabilitation at home after early supported discharge from the Department of Neurology, Huddinge Hospital, for moderately disabled stroke patients in southwest Stockholm. Methods —The patients were eligible if they were continent, independent in feeding, had mental function within normal limits, and had impaired motor function and/or aphasia 1 week after stroke. Patients were randomized either to early supported discharge with continuity of rehabilitation at home for 3 to 4 months or to routine rehabilitation service in a hospital, day care, and/or outpatient care. The home rehabilitation team consisted of two physical therapists, two occupational therapists, and one speech therapist; one of the therapists was assigned as case manager for the patient. The rehabilitation program at home emphasized a task- and context-oriented approach. The activities were chosen on the basis of the patient’s personal interests. Spouses were offered education and individual counseling. A total of 81 patients were followed up for a minimum of 3 months. Patient outcome was assessed by the Frenchay Social Activity Index, Extended Katz Index, Barthel Index, Lindmark Motor Capacity Assessment, Nine-Hole Peg Test, walking speed over 10 m, reported falls, and subjective dysfunction according to the Sickness Impact Profile. Patient use of hospital and home rehabilitation service and patient satisfaction with care were studied. Results —Overall there were no statistical significant differences in outcome. Multivariate logistic regression analysis suggested a systematic positive effect for the home rehabilitation group in social activity, activities of daily living, motor capacity, manual dexterity, and walking. A considerable difference in resource use during such a 3-month period was seen. A 52% reduction in hospitalization was observed: from 29 days in the routine rehabilitation group to 14 days in the home rehabilitation group. Patient satisfaction was in favor of the latter group. Conclusions —Early supported discharge with continuity of home rehabilitation services for the majority of moderately disabled stroke patients during the first 3-month period after acute stroke is not less beneficial than routine rehabilitation and can be a rehabilitation service of choice if follow-up at 6 and 12 months confirms the suggested effectiveness and considerable reduction in use of health care.

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In this paper, we introduce the concept of dense scene flow for visual SLAM applications. Traditional visual SLAM methods assume static features in the environment and that a dominant part of the scene changes only due to camera egomotion. These assumptions make traditional visual SLAM methods prone to failure in crowded real-world dynamic environments with many independently moving objects, such as the typical environments for the visually impaired. By means of a dense scene flow representation, moving objects can be detected. In this way, the visual SLAM process can be improved considerably, by not adding erroneous measurements into the estimation, yielding more consistent and improved localization and mapping results. We show large-scale visual SLAM results in challenging indoor and outdoor crowded environments with real visually impaired users. In particular, we performed experiments inside the Atocha railway station and in the city-center of Alcalá de Henares, both in Madrid, Spain. Our results show that the combination of visual SLAM and dense scene flow allows to obtain an accurate localization, improving considerably the results of traditional visual SLAM methods and GPS-based approaches.

The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system.

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Background and Purpose: This study sought to evaluate early supported discharge and continued rehabilitation at home after stroke, at a minimum of 6 months after the intervention, in terms of patient outcome, resource use and health care cost. Methods: Eighty-three patients, moderately impaired 5–7 days after acute stroke, were included in a randomized controlled trial, 42 being allocated to the intervention and 41 to routine rehabilitation. One-year follow-up of patient outcome included mortality, motor capacity, dysphasia, activities of daily living, social activities, perceived dysfunction, and self-reported falls. Resource use over 12 months included inpatient hospital care, outpatient health care, use of health-related services, informal care, and cost of health care. Results: On univariate analysis there was no difference in patient outcome. Multivariate regression analysis showed that intervention had a significant effect on independence in activities of daily living. A significant difference in inpatient hospital care, initial and recurrent, was observed, with a mean of 18 (intervention) versus 33 days (control) (p = 0.002). Further significant differences were that the control group registered more outpatient visits to hospital occupational therapists (p = 0.02), private physical therapists (p = 0.03) and day-hospital attendance (p = <0.001), while the intervention group registered more visits to nurses in primary care (p = 0.03) and home rehabilitation (p = <0.001). Other differences in outcomes or resource utilization were nonsignificant. Conclusion: In Sweden, early supported discharge with continued rehabilitation at home proved no less beneficial as a rehabilitation service, and provided care and rehabilitation for 5 moderately disabled stroke patients over 12 months after stroke onset for the cost of 4 in routine rehabilitation.

The Parkinson's Disease Sleep Scale (PDSS) is the first published bedside clinical tool to specifically measure sleep disturbances in Parkinson's disease (PD). The objective of the present study was to carry out a metric analysis of a Spanish version (PDSS-SV) using a cross-sectional study of 100 PD patients who participated in the study. Usual measures for PD and mental status were applied by neurologists. Patients completed the Epworth Sleepiness Scale, Parkinson's Disease Questionnaire-39 Items (PDQ-39), and PDSS-SV. PDSS internal consistency (Cronbach's alpha, 0.77; significant item-total correlation for 11 items) was satisfactory. PDSS showed high test-retest reliability (intraclass correlation coefficient for items, 0.79-0.99; for total score, 0.94). Standard error of measurement was 9.80 (crossover) and 5.01 (longitudinal). Scores were distributed uniformly, with low floor and ceiling effect (1%). PDSS scores were correlated significantly with depression (Hamilton Depression Rating Scale, r(S) = -0.55; P < 0.0001) and quality of life (PDQ-39 Summary Index, r(S) = -0.26; P = 0.007), but not with clinical variables. Self-perception of mood disorder, pain, or hallucinations correlated individually with PDSS scores, and a factor explaining 65% of the variance was found. The assessment of PD sleep disorders with the PDSS met some basic standards required for health status measures.

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.