Central neuropathic pain in paraplegia alters movement related potentials

Objectives: Spinal Cord Injured (SCI) persons with and without Central Neuropathic Pain (CNP) show different oscillatory brain activities during imagination of movement. This study investigates whether they also show differences in movement related cortical potentials (MRCP). Methods: SCI paraplegic patients with no CNP (n = 8), with CNP in their lower limbs (n = 8), and healthy control subjects (n = 10) took part in the study. EEG clustering involved independent component analysis, equivalent current dipole fitting, and Measure Projection to define cortical domains that have functional modularity during the motor imagery task. Results: Three domains were identified: limbic system, sensory-motor cortex and visual cortex. The MRCP difference between the groups of SCI with and without CNP was reflected in a domain located in the limbic system, while the difference between SCI patients and control subjects was in the sensorimotor domain. Differences in MRCP morphology between patients and healthy controls were visible for both paralysed and non paralysed limbs. Conclusion: SCI but not CNP affects the movement preparation, and both SCI and CNP affect sensory processes. Significance: Rehabilitation strategies of SCI patients based on MRCP should take into account the presence of CNP

Design and Implementation of Microcontroller Based Portable Drug Delivery System

Portable drug delivery system or portable syringe pump system is a small infusion pump used to gradually deliver drugs, at low doses and at a constant or controllable rate of drug to a patient who needs to take a drug dose regularly in specific periods all the day. The aim of this research is to design and perform a prototype of a portable drug delivery system controlled by micro controller. The micro controller will control the dose of liquid or medication which will be given to the patient and the time of repetition of the dose. The dose rate will be adjusted by controlling the operation of stepper motor which will drive the syringe pump through fine mechanism set

The causality between Electroencephalogram (EEG) and Central Neuropathic Pain (CNP), and the effectiveness of neuromodulation strategies on cortical excitability and CNP in patients with spinal cord injury

Spinal Cord Injury has primary consequences visible immediately upon injury and secondary consequence which develop some time after injury. One of the primary consequences of SCI is loss or impairment of sensory and motor functions. Related secondary consequences of the injury are Central Neuropathic Pain (CNP) and spasticity. Several studies have found that CNP can affect the cortical activity of the patient and long term CNP causes anatomical cortical changes. Therefore, early prediction and treatment of CNP could potentially prevent these changes and hopefully increase responsiveness to the treatment. Neurofeedback (NF) technique, which is a sub-category of biofeedback that uses brain waves as physiological parameters to be modulated, can be used to alter this change in cortical activity and treat CNP. The sensory motor cortex is the area of the brain responsible for voluntary control of movement and for cortical modulation of reflexes. NF provided from the sensory-motor area can therefore affect both CNP and voluntary and reflex movements. The aim of this PhD project was to explore the influence of neuromodulation strategies over the central cortex on the H reflex and CNP following SCI. It also aimed to investigate the causal relationship between the change in EEG activity and the transitional period from early symptoms of CNP to the chronic phase of CNP following SCI. The first study of this project was performed on able-bodied volunteers to explore the effect of the short-term neuromodulation strategies: NF, motor imagery (MI) and mental math (MM) of the sensory-motor rhythm (SMR) on the soleus H reflex. Results of the study showed that it is possible to achieve short-term modulation of the H reflex through short-term modulation of the SMR. Various mental tasks dominantly facilitate the H reflex irrespective of the direction of SMR modulation. The results of this study can be used to explain the effect of NF therapy on spasticity in SCI patient, for example. The second study analysed predictors of CNP in sub-acute SCI patients who have not yet developed physical symptoms of pain. It compared EEG signal between patients who did and did not develop pain within the first six months after EEG recording as well as patients with CNP and able bodied volunteers. This study demonstrated that changes in spontaneous and induced EEG can be both predictors and consequences of CNP following SCI. The third study explores the effectiveness of Neurofeedback (NF) on treatment of CNP in subacute SCI patients with CNP. The results of this study demonstrate that the NF treatment has a positive effect on the reduction of pain, at least over the period of the study. However, numerous factors, and in particular patients’ low prioritization of pain, indicate that early NF of CNP in SCI patients might not be a practical solution. The fourth study utilizes advanced methods of source analysis to define dynamic signatures of long standing CNP by using Measure Projection Analysis (MPA) for movement related cortical potential (MRCP). To separate the effect of long-term paralysis from the effect of long-term CNP, brain activity has been compared between three groups: able bodied volunteers, patients with chronic paraplegia (paralysis of lower limbs) with no pain and patients with chronic paraplegia and long standing CNP. This study showed that the movement related potential is dominantly influenced by paralysis while both CNP and paralysis affect the reafferentation component of the MRCP. Additionally, CNP influences cognitive processes in a manner that depends on the functional area of the cortex

Streaming in-patient BPM data to the cloud with a real-time monitoring system

Monitoring the heart activities for old people or people with medical history (Arrhythmia or CHD) is targeted by most new medical technologies. This paper demonstrated an in-patient real-time monitoring system for heart rate estimation. A ratio of beats per minute (BPM) is continuously recorded, streamed and archived to the cloud via WeMos WiFi development board. This cost effective system is simply based on two sub-systems: BPM data acquisition through pulse sensor and WeMos-based communication systems. The streamed BPM data are saved instantaneously in Google drive as spreadsheets which can only be accessed by authorized persons wherever the internet service is available. Thus, the person in charge can remotely observe the patient’s status and do analytics for the archived data. A pilot study with eight subjects was carried out to validate the developed BPM tele-monitoring system. Encouraging results have been achieved

Prediction of central neuropathic pain in spinal cord injury based on EEG classifier

Objectives: To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with able bodied controls. Methods: Multichannel EEG was recorded in the relaxed eyes opened and eyes closed states in 10 able bodied participants and 31 subacute SCI participants (11 with CNP, 10 without NP and 10 who later developed pain within 6 months of the EEG recording). Up to nine EEG band power features were classified using linear and non-linear classifiers. Results: Three classifiers (artificial neural networks ANN, support vector machine SVM and linear discriminant analysis LDA) achieved similar average performances, higher than 85% on a full set of features identifying patients at risk of developing pain and achieved comparably high performance classifying between other groups. With only 10 channels, LDA and ANN achieved 86% and 83% accuracy respectively, identifying patients at risk of developing CNP. Conclusion: Transferable learning classifier can detect patients at risk of developing CNP. EEG markers of pain appear before its physical symptoms. Simple and complex classifiers have comparable performance. Significance: Identify patients to receive prophylaxic treatment of CNP

The predictive value of cortical activity during motor imagery for subacute spinal cord injury-induced neuropathic pain

Objective: The aim of this study is to explore whether cortical activation and its lateralization during motor imagery (MI) in subacute spinal cord injury (SCI) are indicative of existing or upcoming central neuropathic pain (CNP). Methods: Multichannel electroencephalogram was recorded during MI of both hands in four groups of participants: able-bodied (N=10), SCI and CNP (N=11), SCI who developed CNP within 6 months of EEG recording (N=10), and SCI who remained CNP-free (N=10). Source activations and its lateralization were derived in four frequency bands in 20 regions spanning sensorimotor cortex and pain matrix. Results: Statistically significant differences in lateralization were found in the theta band in premotor cortex (upcoming vs existing CNP, p=0.036), in the alpha band at the insula (healthy vs upcoming CNP, p=0.012), and in the higher beta band at the somatosensory association cortex (no CNP vs upcoming CNP, p=0.042). People with upcoming CNP had stronger activation compared to those with no CNP in the higher beta band for MI of both hands. Conclusions: Activation intensity and lateralization during MI in pain-related areas might hold a predictive value for CNP. Significance: The study increases understanding of the mechanisms underlying transition from asymptomatic to symptomatic early CNP in SCI

Prediction of central neuropathic pain in spinal cord injury based on EEG classifier

Available online 23 May 2018Objectives To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with able bodied controls. Methods Multichannel EEG was recorded in the relaxed eyes opened and eyes closed states in 10 able bodied participants and 31 subacute SCI participants (11 with CNP, 10 without NP and 10 who later developed pain within 6 months of the EEG recording). Up to nine EEG band power features were classified using linear and non-linear classifiers. Results Three classifiers (artificial neural networks ANN, support vector machine SVM and linear discriminant analysis LDA) achieved similar average performances, higher than 85% on a full set of features identifying patients at risk of developing pain and achieved comparably high performance classifying between other groups. With only 10 channels, LDA and ANN achieved 86% and 83% accuracy respectively, identifying patients at risk of developing CNP. Conclusion Transferable learning classifier can detect patients at risk of developing CNP. EEG markers of pain appear before its physical symptoms. Simple and complex classifiers have comparable performance. Significance Identify patients to receive prophylaxic treatment of CNP.This work was partially supported by the Higher Committee for Education Development

Effective connectivity in spinal cord injury-induced neuropathic pain

Aim: The aim of this study was to differentiate the effects of spinal cord injury (SCI) and central neuropathic pain (CNP) on effective connectivity during motor imagery of legs, where CNP is typically experienced. Methods: Multichannel EEG was recorded during motor imagery of the legs in 3 groups of people: able-bodied (N = 10), SCI with existing CNP (N = 10), and SCI with no CNP (N = 20). The last group was followed up for 6 months to check for the onset of CNP. Source reconstruction was performed to obtain cortical activity in 17 areas spanning sensorimotor regions and pain matrix. Effective connectivity was calculated using the directed transfer function in 4 frequency bands and compared between groups. Results: A total of 50% of the SCI group with no CNP developed CNP later. Statistically significant differences in effective connectivity were found between all groups. The differences between groups were not dependent on the frequency band. Outflows from the supplementary motor area were greater for the able-bodied group while the outflows from the secondary somatosensory cortex were greater for the SCI groups. The group with existing CNP showed the least differences from the able-bodied group, appearing to reverse the effects of SCI. The connectivities involving the pain matrix were different between able-bodied and SCI groups irrespective of CNP status, indicating their involvement in motor networks generally. Significance: The study findings might help guide therapeutic interventions targeted at the brain for CNP alleviation as well as motor recovery post SCI

EEG biomarkers of pain and applications of machine learning

No abstract available