Pitfalls to Avoid in Threshold Testing and its Interpretation

2008 ◽  
pp. 269-269-16 ◽  
Author(s):  
RW Bush ◽  
JK Donald ◽  
RJ Bucci
Keyword(s):  
Threshold Testing

Defibrillator Threshold Testing at Generator Replacement: Is it Time to Abandon the Practice?

2015 ◽  
Vol 38 (7) ◽  
pp. 777-781 ◽  
Author(s):  
KEVIN PHAN ◽  
PETER KABUNGA ◽  
MICHAEL J. KILBORN ◽  
RAYMOND W. SY
Keyword(s):  
Threshold Testing ◽  
Generator Replacement

scholarly journals Electrical Perceptual Threshold Testing: A Validation Study

2009 ◽  
Vol 32 (2) ◽  
pp. 140-146 ◽  
Author(s):  
Grace W.S. Leong ◽  
Catherine A. Gorrie ◽  
Karl Ng ◽  
Sue Rutkowski ◽  
Phil M.E. Waite
Keyword(s):  
Validation Study ◽  
Threshold Testing ◽  
Perceptual Threshold

scholarly journals Pengenalan Motif Karawo Menggunakan Ekstraksi Fitur SIFT Dan Approximate Nearest Neighbor

2019 ◽  
Author(s):  
Syahrial
Keyword(s):  
Nearest Neighbor ◽  
Feature Matching ◽  
Recognition Accuracy ◽  
Sift Algorithm ◽  
Approximate Nearest Neighbor ◽  
Single Pattern ◽  
Tree Data ◽  
Threshold Testing ◽  
Root Word ◽  
Tree Data Structure

An art culture from Gorontalo became iconic handcraft is kerawang or karawo. The word “karawo” came from root word of “mokarawo” which means slicing or making holes. It’s created with precision, carefulness, and patience in work using handmade masterpiece. Pattern of karawo itself held four kinds which is flora, fauna, geometric, and nature. From those kinds born vary pattern which come difficult to identify both its names and its kind. Karawo patterns can be form as a single pattern or a pattern that it parts came from several or many pattern combined. Those patterns had its own characteristic from shape and scale perspective. Identifying single pattern on combined pattern are particularly a problem because it’s combined involve scaling and rotation. This research is recognizing single pattern on combined pattern using feature extraction SIFT algorithm which is capable extract feature that invariant from scale and rotation. Feature matching using approximate nearest neighbor (aNN) for similarity of features labor best bin first strategy on kd-tree data structure. Those methods can be a reference to recognize single pattern on combined pattern using from range 5 to 20 match features as a threshold. Testing result indicated recognition accuracy is good which range form 76.36% to 85.45% on recognize the kind of karawo pattern and 76.36% on its name.

scholarly journals Remote Controlled Nociceptive Threshold Testing Systems in Large Animals

2020 ◽  
Author(s):  
Polly Taylor
Keyword(s):  
Home Environment ◽  
Nociceptive Threshold ◽  
Thermal Threshold ◽  
Control Units ◽  
Mechanical Threshold ◽  
Threshold Testing ◽  
The Individual ◽  
Large Animals ◽  
Red Radiation ◽  
Preset Temperature

Nociceptive threshold (NT) testing is widely used for the study of pain and its alleviation. The end point is a normal behavioural response which may be affected by restraint or unfamiliar surroundings leading to erroneous data. Remotely controlled thermal and mechanical NT testing systems were developed to allow free movement during testing and were evaluated in cats, dogs, sheep, horses and camels. Thermal threshold (TT) testing incorporated a heater and temperature sensor held against the animal’s shaved skin. Mechanical threshold (MT) testing incorporated a pneumatic actuator attached to a limb containing a 1 - 2mm radiused pin pushed against the skin. Both stimuli were driven from battery powered control units attached on the animal’s back, controlled remotely via infra-red radiation from a hand held component. Threshold reading was held automatically and displayed digitally on the unit. The system was failsafe with a safety cutout at a preset temperature or force as appropriate. The animals accepted the equipment and behaved normally in their home environment enabling recording of reproducible TT (38.5 – 49.8°C) and MT (2.7 – 10.1N); precise values depended on species, the individual and the stimulus characteristics. Remote controlled NT threshold testing appears to be a viable refinement for pain research.

Differences in sensory processing between chronic cervical zygapophysial joint pain patients with and without cervicogenic headache

Cephalalgia ◽  
2011 ◽  
Vol 31 (8) ◽  
pp. 953-963 ◽  
Author(s):  
Nicholas H L Chua ◽  
Hans A van Suijlekom ◽  
Kris C Vissers ◽  
Lars Arendt-Nielsen ◽  
Oliver H Wilder-Smith
Keyword(s):  
Joint Pain ◽  
Pain Threshold ◽  
Detection Threshold ◽  
Pressure Pain Threshold ◽  
Cervicogenic Headache ◽  
Pain Modulation ◽  
Zygapophysial Joint ◽  
Testing And Measurement ◽  
Threshold Testing ◽  
Pain Patients

Background: It is not known why some patients with underlying chronic nociceptive sources in the neck develop cervicogenic headache (CEH) and why others do not. This quantitative sensory testing (QST) study systematically explores the differences in sensory pain processing in 17 CEH patients with underlying chronic cervical zygapophysial joint pain compared to 10 patients with chronic cervical zygapophysial joint pain but without CEH. Methods: The QST protocol comprises pressure pain threshold testing, thermal detection threshold testing, electrical pain threshold testing and measurement of descending inhibitory modulation using the conditioned pain modulation (CPM) paradigm. Results: The main difference between patients with or without CEH was the lateralization of pressure hyperalgesia to the painful side of the head of CEH patients, accompanied by cold as well as warm relative hyperesthesia on the painful side of the head and neck. Discussion: From this hypothesis-generating study, our results suggest that rostral neuraxial spread of central sensitization, probably to the trigeminal spinal nucleus, plays a major role in the development of CEH.

Sign in / Sign up

Export Citation Format

Share Document