Browsing by Author "Yohanandan, Shivanthan"

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    Balance control systems in Parkinson’s disease and the impact of pedunculopontine area stimulation
    (Brain, 2018-08) Perera, Thushara; Tan, Joy; Cole, Michael; Yohanandan, Shivanthan; Silberstein, Paul; Cook, Raymond; Peppard, Richard; Aziz, Tipu; Coyne, Terry; Brown, Peter; Silburn, Peter; Thevathasan, Wesley
    Impaired balance is a major contributor to falls and diminished quality of life in Parkinson's disease, yet the pathophysiology is poorly understood. Here, we assessed if patients with Parkinson's disease and severe clinical balance impairment have deficits in the intermittent and continuous control systems proposed to maintain upright stance, and furthermore, whether such deficits are potentially reversible, with the experimental therapy of pedunculopontine nucleus deep brain stimulation. Two subject groups were assessed: (i) 13 patients with Parkinson's disease and severe clinical balance impairment, implanted with pedunculopontine nucleus deep brain stimulators; and (ii) 13 healthy control subjects. Patients were assessed in the OFF medication state and blinded to two conditions; off and on pedunculopontine nucleus stimulation. Postural sway data (deviations in centre of pressure) were collected during quiet stance using posturography. Intermittent control of sway was assessed by calculating the frequency of intermittent switching behaviour (discontinuities), derived using a wavelet-based transformation of the sway time series. Continuous control of sway was assessed with a proportional-integral-derivative (PID) controller model using ballistic reaction time as a measure of feedback delay. Clinical balance impairment was assessed using the 'pull test' to rate postural reflexes and by rating attempts to arise from sitting to standing. Patients with Parkinson's disease demonstrated reduced intermittent switching of postural sway compared with healthy controls. Patients also had abnormal feedback gains in postural sway according to the PID model. Pedunculopontine nucleus stimulation improved intermittent switching of postural sway, feedback gains in the PID model and clinical balance impairment. Clinical balance impairment correlated with intermittent switching of postural sway (rho = - 0.705, P < 0.001) and feedback gains in the PID model (rho = 0.619, P = 0.011). These results suggest that dysfunctional intermittent and continuous control systems may contribute to the pathophysiology of clinical balance impairment in Parkinson's disease. Clinical balance impairment and their related control system deficits are potentially reversible, as demonstrated by their improvement with pedunculopontine nucleus deep brain stimulation.
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    Clinical validation of a precision electromagnetic tremor measurement system in participants receiving deep brain stimulation for essential tremor
    (IOP Publishing, 2016-08) Perera, Thushara; Yohanandan, Shivanthan; Thevathasan, Wesley; Jones, Mary; Peppard, Richard; Evans, Andrew; Tan, Joy; McKay, Colette; McDermott, Hugh
    Tremor is characterized commonly through subjective clinical rating scales. Accelerometer-based techniques for objective tremor measurement have been developed in the past, yet these measures are usually presented as an unintuitive dimensionless index without measurement units. Here we have developed a tool (TREMBAL) to provide quantifiable and objective measures of tremor severity using electromagnetic motion tracking. We aimed to compare TREMBAL's objective measures with clinical tremor ratings and determine the test-retest reliability of our technique. Eight participants with ET receiving deep brain stimulation (DBS) therapy were consented. Tremor was simultaneously recorded using TREMBAL and video during DBS adjustment. After each adjustment, participants performed a hands-outstretched task (for postural tremor) and a finger-nose task (for kinetic tremor). Video recordings were de-identified, randomized, and shown to a panel of movement disorder specialists to obtain their ratings. Regression analysis and Pearson's correlations were used to determine agreement between datasets. Subsets of the trial were repeated to assess test-retest reliability. Tremor amplitude and velocity measures were in close agreement with mean clinical ratings (r > 0.90) for both postural and kinetic tremors. Test-retest reliability for both translational and rotational components of tremor showed intra-class correlations >0.80. TREMBAL assessments showed that tremor gradually improved with increasing DBS therapy-this was also supported by clinical observation. TREMBAL measurements are a sensitive, objective and reliable assessment of tremor severity. This tool may have application in clinical trials and in aiding automated optimization of deep brain stimulation.
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    Evaluating machine learning algorithms estimating tremor severity ratings on the Bain-Findley scale
    (IOP Publishing, 2016-11) Yohanandan, Shivanthan; Jones, Mary; Peppard, Richard; Tan, Joy; McDermott, Hugh; Perera, Thushara
    Tremor is a debilitating symptom of some movement disorders. Effective treatment, such as deep brain stimulation (DBS), is contingent upon frequent clinical assessments using instruments such as the Bain–Findley tremor rating scale (BTRS). Many patients, however, do not have access to frequent clinical assessments. Wearable devices have been developed to provide patients with access to frequent objective assessments outside the clinic via telemedicine. Nevertheless, the information they report is not in the form of BTRS ratings. One way to transform this information into BTRS ratings is through linear regression models (LRMs). Another, potentially more accurate method is through machine learning classifiers (MLCs). This study aims to compare MLCs and LRMs, and identify the most accurate model that can transform objective tremor information into tremor severity ratings on the BTRS. Nine participants with upper limb tremor had their DBS stimulation amplitude varied while they performed clinical upper-extremity exercises. Tremor features were acquired using the tremor biomechanics analysis laboratory (TREMBAL). Movement disorder specialists rated tremor severity on the BTRS from video recordings. Seven MLCs and 6 LRMs transformed TREMBAL features into tremor severity ratings on the BTRS using the specialists’ ratings as training data. The weighted Cohen’s kappa ( w) defined the models’ rating accuracy. This study shows that the Random Forest MLC was the most accurate model ( w = 0.81) at transforming tremor information into BTRS ratings, thereby improving the clinical interpretation of tremor information obtained from wearable devices.
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    A simple and inexpensive test-rig for evaluating the performance of motion sensors used in movement disorders research
    (Springer Berlin Heidelberg, 2015-05-29) Perera, Thushara; Yohanandan, Shivanthan; McDermott, Hugh
    Since the advent of electromyogram recording, precise measures of tremor and gait have been used to study movement disorders such as Parkinson’s disease. Now, a wide range of accelerometers and other motion-tracking technologies exist to better inform researchers and clinicians, yet such systems are rarely tested for accuracy or suitability before use. Our inexpensive test-rig can produce sinusoidal displacements using a simple cantilever system driven by a subwoofer. Controlled sinusoids were generated using computer software, and the displacement amplitudes of the test-rig were verified with fiducial marker tracking. To illustrate the use of the test-rig, we evaluated an accelerometer and an electromagnetic motion tracker. Accelerometry recordings were accurate to within ±0.09 g of actual peak-to-peak amplitude with a frequency response close to unity gain between 1 and 20 Hz. The electromagnetic sensor underestimated peak displacement by 2.68 mm, which was largely due to a diminishing gain with increasing frequency. Both sensors had low distortion. Overall sensitivity was limited by noise for the accelerometer and quantisation resolution for the electromagnetic sensor. Our simple and low-cost test-rig can be used to bench-test sensors used in movement disorders research. It was able to produce reliable sinusoidal displacements and worked across the 1- to 20-Hz frequency range.
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    Validation of a Precision Tremor Measurement System for Multiple Sclerosis
    (Elsevier B.V., 2018-09) Perera, Thushara; Lee, Wee-Lih; Yohanandan, Shivanthan; Nguyen, Ai-Lan; Cruse, Belinda; Boonstra, Frederique; Noffs, Gustavo; Vogel, Adam; Kolbe, Scott; Butzkueven, Helmut; Evans, Andrew; van der Walk, Anneke
    Background: Tremor is a debilitating symptom of Multiple Sclerosis (MS). Little is known about its pathophysiology and treatments are limited. Clinical trials investigating new interventions often rely on subjective clinical rating scales to provide supporting evidence of efficacy. New Method: We present a novel instrument (TREMBAL) which uses electromagnetic motion capture technology to quantify MS tremor. We aim to validate TREMBAL by comparison to clinical ratings using regression modelling with 310 samples of tremor captured from 13 MS participants who performed five different hand exercises during several follow-up visits. Minimum detectable change (MDC) and test-retest reliability were calculated and comparisons were made between MS tremor and data from 12 healthy volunteers. Results: Velocity of the index finger was most congruent with clinical observation. Regression modelling combining different features, sensor configurations, and labelling exercises did not improve results. TREMBAL MDC was 84% of its initial measurement compared to 91% for the clinical rating. Intra-class correlations for test-retest reliability were 0.781 for TREMBAL and 0.703 for clinical ratings. Tremor was lower (p = 0.002) in healthy subjects. Comparison with Existing Methods: Subjective scales have low sensitivity, suffer from ceiling effects, and mitigation against inter-rater variability is challenging. Inertial sensors are ubiquitous, however, their output is nonlinearly related to tremor frequency, compensation is required for gravitational artefacts, and their raw data cannot be intuitively comprehended. Conclusions: TREMBAL, compared with clinical ratings, gave measures in agreement with clinical observation, had marginally lower MDC, and similar test-retest reliability.