. Accurate identification of surface electromyography (EMG) muscle onset is vital when examining short temporal parameters such as electromechanical delay. The visual method is considered the 'gold standard' in onset detection. Automatic detection methods are commonly employed to increase objectivity and reduce analysis time, but it is unclear if they are sensitive enough to accurately detect EMG onset when relating them to short-duration motor events.. This study aimed to determine: (1) if automatic detection methods could be used interchangeably with visual methods in detecting EMG onsets (2) if the Teager-Kaiser energy operator (TKEO) as a conditioning step would improve the accuracy of popular EMG onset detection methods. The accuracy of three automatic onset detection methods: approximated generalized likelihood ratio (AGLR), TKEO, and threshold-based method were examined against the visual method. EMG signals from fast, explosive, and slow, ramped isometric plantarflexor contractions were evaluated using each technique.. For fast, explosive contractions, the TKEO was the best-performing automatic detection method, with a low bias level (4.7 ± 5.6 ms) and excellent intraclass correlation coefficient (ICC) of 0.993, however with wide limits of agreement (LoA) (-6.2 to +15.7 ms). For slow, ramped contractions, the AGLR with TKEO conditioning was the best-performing automatic detection method with the smallest bias (11.3 ± 32.9 ms) and excellent ICC (0.983) but produced wide LoA (-53.2 to +75.8 ms). For visual detection, the inclusion of TKEO conditioning improved inter-rater and intra-rater reliability across contraction types compared with visual detection without TKEO conditioning.. In conclusion, the examined automatic detection methods are not sensitive enough to be applied when relating EMG onset to a motor event of short duration. To attain the accuracy needed, visual detection is recommended. The inclusion of TKEO as a conditioning step before visual detection of EMG onsets is recommended to improve visual detection reliability.
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http://dx.doi.org/10.1088/1361-6579/abef56 | DOI Listing |
Eur J Pain
February 2025
Department of Health Science and Technology, Center for Pain and Neuroplasticity (CNAP), SMI, School of Medicine, Aalborg University, Aalborg, Denmark.
Aim: Identify values that could predict the presence of increased pressure-pain sensitivity independent of the migraine cycle through a single assessment.
Methods: This was a secondary analysis of a previous study in which 198 episodic and chronic migraine patients were assessed during all phases of the migraine cycle. Pressure pain threshold (PPT) was assessed over the temporalis, cervical spine, hand, and leg.
Radiol Imaging Cancer
January 2025
From the Department of Radiology (A.C., A.N.Y., R.E., C.H., G.L., M.M., E.B.J., A.L.C., B.G., G.S.K., A.O.), Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy (A.C., A.N.Y., M.M., A.L.C., B.G.), Department of Surgery, Section of Urology (G.G., L.F.R., P.K.M., S.E.), Department of Pathology (T.A.), and Department of Public Health Sciences (M.G.), University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Purpose To evaluate the use of an automated hybrid multidimensional MRI (HM-MRI)-based tool to prospectively identify prostate cancer targets before MRI/US fusion biopsy in comparison with Prostate Imaging and Reporting Data System (PI-RADS)-based multiparametric MRI (mpMRI) evaluation by expert radiologists. Materials and Methods In this prospective clinical trial (ClinicalTrials.gov registration no.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
Shanxi Key Laboratory of Intelligent Detection Technology and Equipment, School of Information and Communication Engineering, North University of China, Taiyuan 030051, Shanxi, China.
Real-time moving target trajectory prediction is highly valuable in applications such as automatic driving, target tracking, and motion prediction. This paper examines the projection of three-dimensional random motion of an object in space onto a sensing plane as an illustrative example. Historical running trajectory data are used to train a reserve network.
View Article and Find Full Text PDFGenome Med
January 2025
Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Background: Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging.
View Article and Find Full Text PDFDig Endosc
January 2025
Department of Gastroenterology, Hiroshima University Hospital, Hiroshima, Japan.
Objectives: We aimed to determine the compliance, safety, and acceptance of colon capsule endoscopy (CCE) and small bowel capsule endoscopy (SBCE) in an out-of-clinic setting remotely supported by medical staff.
Methods: We enrolled 30 examinees (24 with CCE and six with SBCE) who had not undergone CE at six gastroenterological centers. All examinees were provided with instructions on equipment and bowel preparations.
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