A Novel Method of sEMG Signal Segmentation

2013 ◽  
Author(s):  
Lei Shi ◽  
Zhen Liu ◽  
Qiang Wang
Keyword(s):  
Semg Signal ◽  
Signal Segmentation ◽  
Novel Method

scholarly journals A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4729 ◽  
Author(s):  
Taha Khan ◽  
Lina E. Lundgren ◽  
Eric Järpe ◽  
M. Charlotte Olsson ◽  
Pelle Viberg
Keyword(s):  
Random Forest ◽  
Blood Lactate ◽  
Change Point ◽  
Vastus Lateralis ◽  
Lactate Concentration ◽  
Treadmill Running ◽  
Vastus Lateralis Muscle ◽  
Semg Signal ◽  
Novel Method

Blood lactate accumulation is a crucial fatigue indicator during sports training. Previous studies have predicted cycling fatigue using surface-electromyography (sEMG) to non-invasively estimate lactate concentration in blood. This study used sEMG to predict muscle fatigue while running and proposes a novel method for the automatic classification of running fatigue based on sEMG. Data were acquired from 12 runners during an incremental treadmill running-test using sEMG sensors placed on the vastus-lateralis, vastus-medialis, biceps-femoris, semitendinosus, and gastrocnemius muscles of the right and left legs. Blood lactate samples of each runner were collected every two minutes during the test. A change-point segmentation algorithm labeled each sample with a class of fatigue level as (1) aerobic, (2) anaerobic, or (3) recovery. Three separate random forest models were trained to classify fatigue using 36 frequency, 51 time-domain, and 36 time-event sEMG features. The models were optimized using a forward sequential feature elimination algorithm. Results showed that the random forest trained using distributive power frequency of the sEMG signal of the vastus-lateralis muscle alone could classify fatigue with high accuracy. Importantly for this feature, group-mean ranks were significantly different (p < 0.01) between fatigue classes. Findings support using this model for monitoring fatigue levels during running.

scholarly journals Hybrid Brain-Computer Interface: a Novel Method on the Integration of EEG and sEMG Signal for Active Prosthetic Control

2018 ◽  
Vol 22 (1) ◽  
pp. 28
Author(s):  
Reza Darmakusuma ◽  
Ary Setijadi Prihatmanto ◽  
Adi Indrayanto ◽  
Tati Latifah Mengko
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Prosthetic Control ◽  
Semg Signal ◽  
Novel Method

The removal and morphology of intact biofilms from implanted venous access devices

1995 ◽  
Vol 53 ◽  
pp. 1020-1021
Author(s):  
M.A. Gregory ◽  
G.P. Hadley
Keyword(s):  
Patient Selection ◽  
Surgical Oncology ◽  
Venous Access ◽  
Common Procedure ◽  
Indwelling Catheters ◽  
Careful Patient ◽  
Novel Method ◽  
The Subject ◽  
Vascular Catheters ◽  
Venous Access Devices

The insertion of implanted venous access systems for children undergoing prolonged courses of chemotherapy has become a common procedure in pediatric surgical oncology. While not permanently implanted, the devices are expected to remain functional until cure of the primary disease is assured. Despite careful patient selection and standardised insertion and access techniques, some devices fail. The most commonly encountered problems are colonisation of the device with bacteria and catheter occlusion. Both of these difficulties relate to the development of a biofilm within the port and catheter. The morphology and evolution of biofilms in indwelling vascular catheters is the subject of ongoing investigation. To date, however, such investigations have been confined to the examination of fragments of biofilm scraped or sonicated from sections of catheter. This report describes a novel method for the extraction of intact biofilms from indwelling catheters.15 children with Wilm’s tumour and who had received venous implants were studied. Catheters were removed because of infection (n=6) or electively at the end of chemotherapy.

Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 235-245 ◽  
Author(s):  
Katja Franke ◽  
Christian Gaser
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthy Aging ◽  
Brain Aging ◽  
Elderly Subjects ◽  
Additional Increase ◽  
Longitudinal Changes ◽  
Novel Method ◽  
The Brain

We recently proposed a novel method that aggregates the multidimensional aging pattern across the brain to a single value. This method proved to provide stable and reliable estimates of brain aging – even across different scanners. While investigating longitudinal changes in BrainAGE in about 400 elderly subjects, we discovered that patients with Alzheimer’s disease and subjects who had converted to AD within 3 years showed accelerated brain atrophy by +6 years at baseline. An additional increase in BrainAGE accumulated to a score of about +9 years during follow-up. Accelerated brain aging was related to prospective cognitive decline and disease severity. In conclusion, the BrainAGE framework indicates discrepancies in brain aging and could thus serve as an indicator for cognitive functioning in the future.

Sign in / Sign up

Export Citation Format

Share Document