Search results for "Self-Help Devices"

showing 3 items of 3 documents

Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people

2019

Abstract Background Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain act…

AdultMalemedicine.medical_specialtyBrain activity and meditationHealth InformaticsSensory systemNeuroimagingfNIRSWalking050105 experimental psychologylcsh:RC321-571Premotor cortex03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationGait trainingmedicineHumans0501 psychology and cognitive sciencesTreadmilllcsh:Neurosciences. Biological psychiatry. NeuropsychiatryRAGTGaitGait Disorders NeurologicBrain MappingSupplementary motor areabusiness.industryRobotic rehabilitationResearch05 social sciencesRehabilitationGait variabilityBrainRoboticsSelf-Help DevicesGaitExercise Therapymedicine.anatomical_structureGRFNeurorehabilitationFunctional near-infrared spectroscopyFemalebusinessBrain activityhuman activities030217 neurology & neurosurgeryFunctional near-infrared spectroscopyJournal of NeuroEngineering and Rehabilitation
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Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review

2020

Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…

0209 industrial biotechnologyComputer science0206 medical engineeringWalkingReview02 engineering and technologyMachine learningcomputer.software_genrelcsh:Chemical technologyBiochemistryField (computer science)Analytical ChemistryActivity recognition020901 industrial engineering & automationMode (computer interface)Robustness (computer science)Humansassistive deviceslcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationbusiness.industryembedded sensorsSelf-Help Devices020601 biomedical engineeringAtomic and Molecular Physics and Opticslocomotionmachine learningArtificial intelligencebusinesscomputerAlgorithmsSensors
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Resource utilization and productivity loss in persons with spina bifida—an observational study of patients in a tertiary urology clinic in Germany.

2014

Background and purpose To investigate resource use and burden associated with spina bifida (SB) in Germany. Methods A questionnaire was used to obtain information on SB-related healthcare resource use and assistive technologies used for the last 1 and 10 years. Individuals with SB were recruited at a tertiary specialist clinic. To participate, persons with SB required the cognitive ability to respond or a caregiver to answer questions on their behalf. They could use personal medical charts or other records to answer. The analyses included assessment of frequency and extent of resource use for both time frames. Results Data on 88 persons with a diagnosis of SB were collected (44% female). Du…

AdultMalemedicine.medical_specialtyTertiary Care CentersCost of IllnessGermanyHealth caremedicineHumansSpinal DysraphismHospital daysbusiness.industrySpina bifidaHealth Servicesmedicine.diseaseSelf-Help DevicesHospitalizationNeurologyPhysical therapyUrology clinicResource useObservational studyFemaleNeurology (clinical)businessHealthcare providersResource utilizationEuropean journal of neurology
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