The authors tested for 1/f noise in motor imagery (MI). Participants pointed and imagined pointing to a single target (Experiment 1), to targets of varied size (Experiment 2), and switched between pointing and grasping (Experiment 3). Experiment 1 showed comparable patterns of serial correlation in actual and imagined movement. Experiment 2 suggested increased correlation for MI and performance with increased task difficulty, perhaps reflecting adaptation to a more complex environment. Experiment 3 suggested a parallel decrease in correlation with task switching, perhaps reflecting discontinuity of mental set. Although present results do not conclusively reveal 1/f fluctuation, the emergent patterns suggest that MI could incorporate trial-to-trial error across a range of constraints.
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http://dx.doi.org/10.1080/00222895.2010.497511 | DOI Listing |
Environ Monit Assess
January 2025
Technische Hochschule Nürnberg Georg Simon Ohm, Institute of Hydraulic Engineering and Water Resources Management, Nuremberg, Germany.
Through the mobilization of movable objects due to the extreme hydraulic conditions during a flood event, blockages, damage to infrastructure, and endangerment of human lives can occur. To identify potential hazards from aerial imagery and take appropriate precautions, a change detection tool (CDT) was developed and tested using a study area along the Aisch River in Germany. The focus of the CDT development was on near real-time analysis of point cloud data generated by structure from motion from aerial images of temporally separated surveys, enabling rapid and targeted implementation of measures.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Rehabilitation, University Hospital Olomouc, Olomouc, Czech Republic.
Motor imagery (MI) is a mental simulation of a movement without its actual execution. Our study aimed to assess how MI of two modalities of gait (normal gait and much more posturally challenging slackline gait) affects muscle activity and lower body kinematics. Electromyography (biceps femoris, gastrocnemius medialis, rectus femoris and tibialis anterior muscles) as well as acceleration and angular velocity (shank, thigh and pelvis segments) data were collected in three tasks for both MI modalities of gait (rest, gait imagery before and after the real execution of gait) in quiet bipedal stance in 26 healthy young adults.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, University of Acibadem Mehmet Ali Aydınlar, Kerem Aydinlar Kampusu, Icerenkoy Mah. Kayisdagi Cad. No: 32, Atasehir, 34752, Istanbul, Turkey.
This systematic review and meta-analysis aims to assess the effects of movement representation techniques (MRT) on pain, range of motion, functional outcomes, and pain-related fear in patients with non-specific shoulder pain (NSSP). A literature search conducted in PubMed, PEDro, EBSCO, Scopus, Cochrane Library, ScienceDirect, and gray literature on April 31, 2023. We selected seven randomized controlled trials based on the PICOS framework.
View Article and Find Full Text PDFPhysiol Rep
January 2025
Gravitational Physiology and Medicine Research Unit, Division of Physiology, Otto Loewi Research Center, Medical University of Graz, Graz, Austria.
Available evidence suggests that various medical/rehabilitation treatments evoke multiple effects on blood hemostasis. It was therefore the aim of our study to examine whether fascial manipulation, vibration exercise, motor imagery, or neuro-muscular electrical stimulation can activate the coagulation system, and, thereby, expose patients to thrombotic risk. Ten healthy young subject were enrolled in the study.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Department of Biomedical Engineering, Izmir Katip Celebi University, Izmir, Türkiye.
Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have already proven useful to that effect, the use of many features and ineffective EEG channels often leads to a complex structure of classifier algorithms.
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