scholarly journals Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach

2018 ◽  
Vol 38 (33) ◽  
pp. 7293-7302 ◽  
Author(s):  
Anton Rogachov ◽  
Joshua C. Cheng ◽  
Kasey S. Hemington ◽  
Rachael L. Bosma ◽  
Junseok A. Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chronic Pain ◽  
Low Frequency ◽  
Learning Approach ◽  
Low Frequency Oscillations ◽  
Chronic Pain Patients ◽  
Machine Learning Approach ◽  
Pain Ratings ◽  
Pain Patients

scholarly journals Predicting Vasovagal Responses: A Model-Based and Machine Learning Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Theodore Raphan ◽  
Sergei B. Yakushin
Keyword(s):  
Machine Learning ◽  
Beta Blockers ◽  
Vasovagal Syncope ◽  
Low Frequency ◽  
Tilt Test ◽  
Learning Approach ◽  
Clear Understanding ◽  
Low Frequency Oscillations ◽  
Separating Hyperplane ◽  
Machine Learning Approach

Vasovagal syncope (VVS) or neurogenically induced fainting has resulted in falls, fractures, and death. Methods to deal with VVS are to use implanted pacemakers or beta blockers. These are often ineffective because the underlying changes in the cardiovascular system that lead to the syncope are incompletely understood and diagnosis of frequent occurrences of VVS is still based on history and a tilt test, in which subjects are passively tilted from a supine position to 20° from the spatial vertical (to a 70° position) on the tilt table and maintained in that orientation for 10–15 min. Recently, is has been shown that vasovagal responses (VVRs), which are characterized by transient drops in blood pressure (BP), heart rate (HR), and increased amplitude of low frequency oscillations in BP can be induced by sinusoidal galvanic vestibular stimulation (sGVS) and were similar to the low frequency oscillations that presaged VVS in humans. This transient drop in BP and HR of 25 mmHg and 25 beats per minute (bpm), respectively, were considered to be a VVR. Similar thresholds have been used to identify VVR's in human studies as well. However, this arbitrary threshold of identifying a VVR does not give a clear understanding of the identifying features of a VVR nor what triggers a VVR. In this study, we utilized our model of VVR generation together with a machine learning approach to learn a separating hyperplane between normal and VVR patterns. This methodology is proposed as a technique for more broadly identifying the features that trigger a VVR. If a similar feature identification could be associated with VVRs in humans, it potentially could be utilized to identify onset of a VVS, i.e, fainting, in real time.

scholarly journals Extended reality for chronic pain relief

2020 ◽  
Author(s):  
J Wang ◽  
Craig Anslow ◽  
Brian Robinson ◽  
Simon McCallum
Keyword(s):  
Chronic Pain ◽  
Pain Relief ◽  
Body Movement ◽  
Daily Lives ◽  
Chronic Pain Patients ◽  
Pain Ratings ◽  
Subjective Pain ◽  
Initial Injury ◽  
Physical Interactions ◽  
Pain Patients

© 2019 Copyright held by the owner/author(s). Chronic pain is ongoing pain lasting for long periods of time after the initial injury or disease has healed. Chronic pain is difficult to treat and can affect the daily lives of patients. Distraction therapy is a proven way of relieving pain by redirecting the focus of patients' attention. Virtual reality is an effective platform for distraction therapy as it immerses the user visually, aurally, and even somewhat physically in a virtual world detached from reality. There is little research done on the effects that physical interactions have on pain management. This project aims to evaluate different types of extended reality (XR) interactions, including full body movement, for chronic pain patients to determine which is the best for pain relief. We are building a prototype for participants to interact both mentally and physically and measuring the reduction in subjective pain ratings at various points of the XR experience.

The effects of evaluation, narcotics and behavioral treatment on pain ratings in chronic pain patients

Pain ◽  
1984 ◽  
Vol 18 ◽  
pp. S423
Author(s):  
Daniel M. Doleys ◽  
Jeffrey Dolce ◽  
Annette Doleys ◽  
Maureen Crocker ◽  
Susan Wolfe
Keyword(s):  
Chronic Pain ◽  
Behavioral Treatment ◽  
Chronic Pain Patients ◽  
Pain Ratings ◽  
Pain Patients

scholarly journals Using a machine learning approach to identify low-frequency and rare filaggrin alleles associated with remission of atopic dermatitis

2021 ◽  
pp. 100046
Author(s):  
Ronald Berna ◽  
Nandita Mitra ◽  
Ole Hoffstad ◽  
Bradley Wubbenhorst ◽  
Katherine L. Nathanson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Atopic Dermatitis ◽  
Low Frequency ◽  
Learning Approach ◽  
Machine Learning Approach

scholarly journals Cortico-autonomic local arousals and heightened somatosensory arousability during NREM sleep of mice in neuropathic pain

2021 ◽  
Author(s):  
Anita Lüthi ◽  
Romain Cardis ◽  
Sandro Lecci ◽  
Laura MJ Fernandez ◽  
Alejandro Osorio-Forero ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Neuropathic Pain ◽  
Sleep Disturbances ◽  
Low Frequency ◽  
Nrem Sleep ◽  
Rapid Eye Movement Sleep ◽  
Sleep Complaints ◽  
Chronic Pain Patients ◽  
Neurophysiological Mechanisms ◽  
Pain Patients

Chronic pain patients frequently suffer from sleep disturbances. Improvement of sleep quality alleviates pain, but neurophysiological mechanisms underlying sleep disturbances require clarification to advance therapeutic strategies. Chronic pain causes high-frequency electrical activity in pain-processing cortical areas that could disrupt the normal process of low-frequency sleep rhythm generation. We found that the spared-nerve-injury (SNI) mouse model, mimicking human neuropathic pain, had preserved sleep-wake behavior. However, when we probed spontaneous arousability based on infraslow continuity-fragility dynamics of non-rapid-eye-movement sleep (NREMS), we found more numerous local cortical arousals accompanied by heart rate increases in hindlimb primary somatosensory, but not in prelimbic, cortices of SNI mice. Closed-loop mechanovibrational stimulation revealed higher sensory arousability in SNI. Sleep in chronic pain thus looked preserved in conventional measures but showed elevated spontaneous and evoked arousability. Our findings develop a novel moment-to-moment probing of NREMS fragility and propose that chronic pain-induced sleep complaints arise from perturbed arousability.

scholarly journals Extended reality for chronic pain relief

2020 ◽  
Author(s):  
J Wang ◽  
Craig Anslow ◽  
Brian Robinson ◽  
Simon McCallum
Keyword(s):  
Chronic Pain ◽  
Pain Relief ◽  
Body Movement ◽  
Daily Lives ◽  
Chronic Pain Patients ◽  
Pain Ratings ◽  
Subjective Pain ◽  
Initial Injury ◽  
Physical Interactions ◽  
Pain Patients

© 2019 Copyright held by the owner/author(s). Chronic pain is ongoing pain lasting for long periods of time after the initial injury or disease has healed. Chronic pain is difficult to treat and can affect the daily lives of patients. Distraction therapy is a proven way of relieving pain by redirecting the focus of patients' attention. Virtual reality is an effective platform for distraction therapy as it immerses the user visually, aurally, and even somewhat physically in a virtual world detached from reality. There is little research done on the effects that physical interactions have on pain management. This project aims to evaluate different types of extended reality (XR) interactions, including full body movement, for chronic pain patients to determine which is the best for pain relief. We are building a prototype for participants to interact both mentally and physically and measuring the reduction in subjective pain ratings at various points of the XR experience.

Intraindividual Variability in Daily Sleep and Pain Ratings Among Chronic Pain Patients

2011 ◽  
Vol 27 (5) ◽  
pp. 425-433 ◽  
Author(s):  
Erin M. OʼBrien ◽  
Lori B. Waxenberg ◽  
James W. Atchison ◽  
Henry A. Gremillion ◽  
Roland M. Staud ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Intraindividual Variability ◽  
Chronic Pain Patients ◽  
Pain Ratings ◽  
Pain Patients

Pain Influences Several Levels of Attention

2005 ◽  
Vol 16 (4) ◽  
pp. 235-242 ◽  
Author(s):  
Astrid von Bueren Jarchow ◽  
Bogdan P. Radanov ◽  
Lutz Jäncke
Keyword(s):  
Chronic Pain ◽  
Divided Attention ◽  
Covert Attention ◽  
Attention Task ◽  
Attentional Deficits ◽  
Control Subjects ◽  
Chronic Pain Patients ◽  
Divided Attention Task ◽  
Pain Stimuli ◽  
Pain Patients

Abstract: The aim of the present study was to examine to what extent chronic pain has an impact on various attentional processes. To measure these attention processes a set of experimental standard tests of the “Testbatterie zur Aufmerksamkeitsprüfung” (TAP), a neuropsychological battery testing different levels of attention, were used: alertness, divided attention, covert attention, vigilance, visual search, and Go-NoGo tasks. 24 chronic outpatients and 24 well-matched healthy control subjects were tested. The control subjects were matched for age, gender, and education. The group of chronic pain patients exhibited marked deficiencies in all attentional functions except for the divided attention task. Thus, the data supports the notion that chronic pain negatively influences attention because pain patients` attention is strongly captivated by the internal pain stimuli. Only the more demanding divided attention task has the capability to distract the focus of attention to the pain stimuli. Therefore, the pain patients are capable of performing within normal limits. Based on these findings chronic pain patients' attentional deficits should be appropriately evaluated and considered for insurance and work related matters. The effect of a successful distraction away from the pain in the divided attention task can also open new therapeutic aspects.

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