scholarly journals A Framework for (Tele-) Monitoring of the Rehabilitation Progress in Stroke Patients

2015 ◽  
Vol 06 (04) ◽  
pp. 757-768 ◽  
Author(s):  
V. David ◽  
M. Haller ◽  
S. Kotzian ◽  
M. Hofmann ◽  
S. Schlossarek ◽  
...  
Keyword(s):  
Automated Analysis ◽  
Web Interface ◽  
Tablet Pc ◽  
Monitoring Tool ◽  
Stroke Patients ◽  
Assessment Tests ◽  
Movement Data ◽  
Automated Evaluation ◽  
Independent Life ◽  
Tele Monitoring

SummaryBackground: Preservation of mobility in conjunction with an independent life style is one of the major goals of rehabilitation after stroke.Objectives: The Rehab@Home framework shall support the continuation of rehabilitation at home.Methods: The framework consists of instrumented insoles, connected wirelessly to a 3G ready tablet PC, a server, and a web-interface for medical experts. The rehabilitation progress is estimated via automated analysis of movement data from standardized assessment tests which are designed according to the needs of stroke patients and executed via the tablet PC application.Results: The Rehab@Home framework’s implementation is finished and ready for the field trial (at five patients’ homes). Initial testing of the automated evaluation of the standardized mobility tests shows reproducible results.Conclusions: Therefore it is assumed that the Rehab@Home framework is applicable as monitoring tool for the gait rehabilitation progress in stroke patients.

scholarly journals Effects of Mirror Therapy Using a Tablet PC on Central Facial Paresis in Stroke Patients

2017 ◽  
Vol 41 (3) ◽  
pp. 347 ◽  
Author(s):  
Jung-A Kang ◽  
Min Ho Chun ◽  
Su Jin Choi ◽  
Min Cheol Chang ◽  
You Gyoung Yi
Keyword(s):  
Mirror Therapy ◽  
Tablet Pc ◽  
Facial Paresis ◽  
Stroke Patients

Web-Based Assessment of CAD Data in Undergraduate Design Education

2014 ◽  
Author(s):  
Daniel Benjamin Krüger ◽  
Sandro Wartzack
Keyword(s):  
Design Education ◽  
Automated Analysis ◽  
Web Interface ◽  
Web Based ◽  
Teaching Concept ◽  
Hybrid Teaching ◽  
E Learning ◽  
Conventional Classroom ◽  
Modeling Task

In this contribution a web-based assessment framework for CAD data is proposed which has been developed based on the experience the authors made giving undergraduate courses at a German university. The framework is the backbone of a hybrid teaching concept combining conventional classroom lessons with e-learning elements. In-between the classroom lessons the students receive instructions on a particular modeling task via a web-interface. The same interface is used to hand in solutions in form of CAD files. Teachers who need to assess these solutions are supported by a semi-automated analysis of the CAD geometry. An algorithm compares each solution with a reference solution in order to reveal typical modeling mistakes. After the assessment is completed the students receive a feedback on their work. A case study on the application of the teaching concept in a course with 691 participants held during summer term 2013 reveals the positive experience the authors made using the system and points to some issues that need to be improved in the future.

scholarly journals Visual analytics of sensor movement data for cheetah behaviour analysis

2021 ◽  
Author(s):  
Karsten Klein ◽  
Sabrina Jaeger ◽  
Jörg Melzheimer ◽  
Bettina Wachter ◽  
Heribert Hofer ◽  
...  
Keyword(s):  
Visual Analytics ◽  
Visual Analysis ◽  
Automated Analysis ◽  
Environmental Data ◽  
Impact Factors ◽  
Data Sets ◽  
Movement Data ◽  
Data Loggers ◽  
Intuitive Interfaces ◽  
Gps Data Loggers

Abstract Current tracking technology such as GPS data loggers allows biologists to remotely collect large amounts of movement data for a large variety of species. Extending, and often replacing interpretation based on observation, the analysis of the collected data supports research on animal behaviour, on impact factors such as climate change and human intervention on the globe, as well as on conservation programs. However, this analysis is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, for example, for the detection of behavioural patterns, and human inspection, for example, for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. For this analysis and inspection, the movement data needs to be put into the context of environmental data, which helps to interpret the behaviour. Thus, a major challenge is to design and develop methods and intuitive interfaces that integrate the data for analysis by biologists. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments. Graphic abstract

A Test Battery to Measure the Recovery of Voluntary Movement Control following Stroke

1988 ◽  
Vol 51 (1) ◽  
pp. 11-14 ◽  
Author(s):  
Ailie J Turton ◽  
Carole M Fraser
Keyword(s):  
Activities Of Daily Living ◽  
Upper Limb ◽  
Daily Living ◽  
Voluntary Movement ◽  
Movement Control ◽  
Stroke Patients ◽  
Post Stroke ◽  
Assessment Tests ◽  
Upper Limb Function ◽  
Selection Of

Tests of upper limb function and an activities of daily living (ADL) index were selected to measure recovery following stroke. Thirty stroke patients were assessed at intervals for up to 6 months to 1 year post-stroke using the battery. The results showed that the ADL index is insensitive to upper limb recovery. All the tests measured recovery in some of the patients after 24 weeks post-stroke. Since the presentation and recovery of patients was variable, it is argued that it is necessary to offer a selection of assessment tests to measure recovery and to aid treatment planning.

scholarly journals Gait Event Detection for Stroke Patients during Robot-Assisted Gait Training

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3399
Author(s):  
Andreas Schicketmueller ◽  
Juliane Lamprecht ◽  
Marc Hofmann ◽  
Michael Sailer ◽  
Georg Rose
Keyword(s):  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Gait Training ◽  
Patient Specific ◽  
Stroke Patients ◽  
Robot Assisted ◽  
Rehabilitation Process ◽  
Type 1 Error ◽  
Movement Data ◽  
Measurement Units

Functional electrical stimulation and robot-assisted gait training are techniques which are used in a clinical routine to enhance the rehabilitation process of stroke patients. By combining these technologies, therapy effects could be further improved and the rehabilitation process can be supported. In order to combine these technologies, a novel algorithm was developed, which aims to extract gait events based on movement data recorded with inertial measurement units. In perspective, the extracted gait events can be used to trigger functional electrical stimulation during robot-assisted gait training. This approach offers the possibility of equipping a broad range of potential robot-assisted gait trainers with functional electrical stimulation. In particular, the aim of this study was to test the robustness of the previously developed algorithm in a clinical setting with patients who suffered a stroke. A total amount of N = 10 stroke patients participated in the study, with written consent. The patients were assigned to two different robot-assisted gait trainers (Lyra and Lokomat) according to their performance level, resulting in five recording sessions for each gait-trainer. A previously developed algorithm was applied and further optimized in order to extract the gait events. A mean detection rate across all patients of 95.8% ± 7.5% for the Lyra and 98.7% ± 2.6% for the Lokomat was achieved. The mean type 1 error across all patients was 1.0% ± 2.0% for the Lyra and 0.9% ± 2.3% for the Lokomat. As a result, the developed algorithm was robust against patient specific movements, and provided promising results for the further development of a technique that can detect gait events during robot-assisted gait training, with the future aim to trigger functional electrical stimulation.

scholarly journals The effects of golf training in patients with stroke: a pilot study

2015 ◽  
Vol 27 (5) ◽  
pp. 865-873 ◽  
Author(s):  
Tobias Schachten ◽  
Petra Jansen
Keyword(s):  
Experimental Period ◽  
Training Group ◽  
Well Being ◽  
Berg Balance Scale ◽  
Control Group ◽  
Stroke Patients ◽  
Balance Test ◽  
Assessment Tests ◽  
Visual Spatial ◽  
Before And After

ABSTRACTBackground:Stroke is the most common neurological disease and the primary cause of lifelong disability in industrialized countries. Because of this it is important to investigate any kind of successful therapy.Methods:From the 24 recruited stroke patients who were between 23 and 72 years old, 14 patients were separated either in a golf training group (EG), or a social communication meeting (CG). Both groups met for one hour sessions, twice a week, for ten weeks. All participants completed assessment tests before and after the experimental period: cognitive tests measuring attention (Go/No-Go task), visual-spatial memory (Block-Tapping test) and mental rotation performance (MRT); a balance test (Berg Balance Scale), and an emotional well-being test (CES-D-Scale).Results:The results show that both groups improved in the CES Scale, the block-tapping test and the balance test. In addition, stroke patients who received a golf training showed a significant improvement in the MRT comparing to the control group (CG).Conclusion:It is indicated that golf training can improve visual imagery ability in stroke patients, even late after stroke.

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