Fractal measures of video-recorded trajectories can classify motor subtypes in Parkinson’s disease

[Abstract] Parkinson’s Disease is one of the most prevalent neurodegenerative diseases in the world and affects millions of individuals worldwide. The clinical criteria for classification of motor subtypes in Parkinson’s Disease are subjective and may be misleading when symptoms are not clearly identifiable. A video recording protocol was used to measure hand tremor of 14 individuals with Parkinson’s Disease and 7 healthy subjects. A method for motor subtype classification was proposed based on the spectral distribution of the movement and compared with the existing clinical criteria. Box-counting dimension and Hurst Exponent calculated from the trajectories were used as the relevant measures for the statistical tests. The classification based on the power-spectrum is shown to be well suited to separate patients with and without tremor from healthy subjects and could provide clinicians with a tool to aid in the diagnosis of patients in an early stage of the disease.Brasil. Conselho Nacional de Desenvolvimento Científico e Tecnológico; 306571/2011-0Brasil. Conselho Nacional de Desenvolvimento Científico e Tecnológico; 481414/2012-

Estimation of Physiological Tremor from Accelerometers for Real-Time Applications

Accurate filtering of physiological tremor is extremely important in robotics assisted surgical instruments and procedures. This paper focuses on developing single stage robust algorithms for accurate tremor filtering with accelerometers for real-time applications. Existing methods rely on estimating the tremor under the assumption that it has a single dominant frequency. Our time-frequency analysis on physiological tremor data revealed that tremor contains multiple dominant frequencies over the entire duration rather than a single dominant frequency. In this paper, the existing methods for tremor filtering are reviewed and two improved algorithms are presented. A comparative study is conducted on all the estimation methods with tremor data from microsurgeons and novice subjects under different conditions. Our results showed that the new improved algorithms performed better than the existing algorithms for tremor estimation. A procedure to separate the intended motion/drift from the tremor component is formulated

Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data

This paper presents a two stage algorithm for real-time estimation of instantaneous tremor parameters from gyroscope recordings. Gyroscopes possess the advantage of providing directly joint rotational speed, overcoming the limitations of traditional tremor recording based on accelerometers. The proposed algorithm first extracts tremor patterns from raw angular data, and afterwards estimates its instantaneous amplitude and frequency. Real-time separation of voluntary and tremorous motion relies on their different frequency contents, whereas tremor modelling is based on an adaptive LMS algorithm and a Kalman filter. Tremor parameters will be employed to drive a neuroprosthesis for tremor suppression based on biomechanical loading

The diagnostic value of clinical neurophysiology in hyperkinetic movement disorders:A systematic review

Introduction: To guide the neurologist and neurophysiologist with interpretation and implementation of clinical neurophysiological examinations, we aim to provide a systematic review on evidence of electrophysiological features used to differentiate between hyperkinetic movement disorders. Methods: A PRISMA systematic search and QUADAS quality evaluation has been performed in PubMed to identify diagnostic test accuracy studies comparing electromyography and accelerometer features. We included papers focusing on tremor, dystonia, myoclonus, chorea, tics and ataxia and their functional variant. The features were grouped as 1) basic features (e.g., amplitude, frequency), 2) the influence of tasks on basic features (e.g., entrainment, distraction), 3) advanced analyses of multiple signals, 4) and diagnostic tools combining features. Results: Thirty-eight cross-sectional articles were included discussing tremor (n = 28), myoclonus (n = 5), dystonia (n = 5) and tics (n = 1). Fifteen were rated as ‘high quality’. In tremor, the basic and task-related features showed great overlap between clinical tremor syndromes, apart from rubral and enhanced physiological tremor. Advanced signal analyses were best suited for essential, parkinsonian and functional tremor, and cortical, non-cortical and functional jerks. Combinations of electrodiagnostic features could identify essential, enhanced physiological and functional tremor. Conclusion: Studies into the diagnostic accuracy of electrophysiological examinations to differentiate between hyperkinetic movement disorders have predominantly been focused on clinical tremor syndromes. No single feature can differentiate between them all; however, a combination of analyses might improve diagnostic accuracy

Systematic clinical approach for diagnosing upper limb tremor

Tremor is the most common movement disorder worldwide, but diagnosis is challenging. In 2018, the task force on tremor of the International Parkinson and Movement Disorder Society published a consensus statement that proposes a tremor classification along two independent axes: a clinical tremor syndrome and its underlying aetiology. In line with this statement, we here propose a stepwise diagnostic approach that leads to the correct clinical and aetiological classification of upper limb tremor. We also describe the typical clinical signs of each clinical tremor syndrome. A key feature of our algorithm is the distinction between isolated and combined tremor syndromes, in which tremor is accompanied by bradykinesia, cerebellar signs, dystonia, peripheral neuropathy or brainstem signs. This distinction subsequently informs the selection of appropriate diagnostic tests, such as neurophysiology, laboratory testing, structural and dopaminergic imaging and genetic testing. We highlight treatable metabolic causes of tremor, as well as drugs and toxins that can provoke tremor. The stepwise approach facilitates appropriate diagnostic testing and avoids unnecessary investigations. We expect that the approach offered in this article will reduce diagnostic uncertainty and increase the diagnostic yield in patients with tremor

A Low Cost Wireless Sensor Interface for the Quantification of Tremor in Parkinson’s Disease

Deep brain stimulation surgery involves placing an electrode in the deep brain to suppress the motor symptoms of patients with Parkinson’s disease (PD). Currently physicians use the standard Unified Parkinson’s Disease Rating Scale to describe the tremor. This scale involves subjective anchor-based observations by the clinical expert. A wireless accelerometer system is presented that was built from off the shelf components to objectively quantify tremor scores. The system consists of a Teensy microcontroller and two accelerometers. It wirelessly transmits the readings through a Bluetooth module. The data is received by a custom C/C++ that parses and transmits the data to the Simulink environment for realtime visualization and analysis. The system is used to record data from patients with PD during and after DBS surgery. In this thesis, we describe the wireless accelerometer system in detail and study the correlation of sensor readings with UPDRS scores in the different DBS states. In particular, we provide data showing that such a system can be used for the objective quantification of tremor symptoms in PD patients.Biomedical Engineering, Department o

ESTIMATION OF STRETCH REFLEX CONTRIBUTIONS OF WRIST USING SYSTEM IDENTIFICATION AND QUANTIFICATION OF TREMOR IN PARKINSON'S DISEASE PATIENTS

"The brain's motor control can be studied by characterizing the activity of spinal motor nuclei to brain control, expressed as motor unit activity recordable by surface electrodes". When a specific area is under consideration, the first step in investigation of the motor control system pertinent to it is the system identification of that specific body part or area. The aim of this research is to characterize the working of the brain's motor control system by carrying out system identification of the wrist joint area and quantifying tremor observed in Parkinson's disease patients. We employ the ARMAX system identification technique to gauge the intrinsic and reflexive components of wrist stiffness, in order to facilitate analysis of problems associated with Parkinson's disease. The intrinsic stiffness dynamics comprise majority of the total stiffness in the wrist joint and the reflexive stiffness dynamics contribute to the tremor characteristic commonly found in Parkinson's disease patients. The quantification of PD tremor entails using blind source separation of convolutive mixtures to obtain sources of tremor in patients suffering from movement disorders. The experimental data when treated with blind source separation reveals sources exhibiting the tremor frequency components of 3-8 Hz. System identification of stiffness dynamics and assessment of tremor can reveal the presence of additional abnormal neurological signs and early identification or diagnosis of these symptoms would be very advantageous for clinicians and will be instrumental to pave the way for better treatment of the disease

The nature of tremor circuits in parkinsonian and essential tremor

Tremor is a cardinal feature of Parkinson’s disease and essential tremor, the two most common movement disorders. Yet, the mechanisms underlying tremor generation remain largely unknown. We hypothesized that driving deep brain stimulation electrodes at a frequency closely matching the patient’s own tremor frequency should interact with neural activity responsible for tremor, and that the effect of stimulation on tremor should reveal the role of different deep brain stimulation targets in tremor generation. Moreover, tremor responses to stimulation might reveal pathophysiological differences between parkinsonian and essential tremor circuits. Accordingly, we stimulated 15 patients with Parkinson’s disease with either thalamic or subthalamic electrodes (13 male and two female patients, age: 50–77 years) and 10 patients with essential tremor with thalamic electrodes (nine male and one female patients, age: 34–74 years). Stimulation at near-to tremor frequency entrained tremor in all three patient groups (ventrolateral thalamic stimulation in Parkinson’s disease, P = 0.0078, subthalamic stimulation in Parkinson’s disease, P = 0.0312; ventrolateral thalamic stimulation in essential tremor, P = 0.0137; two-tailed paired Wilcoxon signed-rank tests). However, only ventrolateral thalamic stimulation in essential tremor modulated postural tremor amplitude according to the timing of stimulation pulses with respect to the tremor cycle (e.g. P = 0.0002 for tremor amplification, two-tailed Wilcoxon rank sum test). Parkinsonian rest and essential postural tremor severity (i.e. tremor amplitude) differed in their relative tolerance to spontaneous changes in tremor frequency when stimulation was not applied. Specifically, the amplitude of parkinsonian rest tremor remained unchanged despite spontaneous changes in tremor frequency, whereas that of essential postural tremor reduced when tremor frequency departed from median values. Based on these results we conclude that parkinsonian rest tremor is driven by a neural network, which includes the subthalamic nucleus and ventrolateral thalamus and has broad frequency-amplitude tolerance. We propose that it is this tolerance to changes in tremor frequency that dictates that parkinsonian rest tremor may be significantly entrained by low frequency stimulation without stimulation timing-dependent amplitude modulation. In contrast, the circuit influenced by low frequency thalamic stimulation in essential tremor has a narrower frequency-amplitude tolerance so that tremor entrainment through extrinsic driving is necessarily accompanied by amplitude modulation. Such differences in parkinsonian rest and essential tremor will be important in selecting future strategies for closed loop deep brain stimulation for tremor control

Die Gangstörung bei Patienten mit orthostatischem Tremor

Der primäre orthostatische Tremor ist eine seltene Erkrankung, die einen hochfrequenten Tremor von 13-18 Hz der unteren Extremität beim Stehen aufweist mit einer Symptomlinderung beim Sitzen, Gehen oder Hinlegen. Der Erkrankung liegt ein pathologisches, ponto-zerebello-thalamo-kortikales Tremornetzwerk zugrunde, das auch im Liegen weiter aktiviert bleibt. Im Zusammenhang mit dieser Erkrankung befasst sich diese Dissertation mit folgenden Fragestellungen: 1) Wie verändert sich der Tremor bei der Transition vom Stehen zum Gehen? 2) Gibt es eine objektivierbare Gangstörung trotz subjektiver Symptomregredienz beim Gehen? 3) Kann der Tremor durch propriozeptive Reize moduliert und gegebenenfalls gelindert werden? In einer klinischen Untersuchung mittels eines drucksensitiven Laufbands und Oberflächen-Elektromyographie konnte gezeigt werden, dass der Tremor während des Gehens persistiert mit einer zwischenzeitlichen Verlagerung der Tremorfrequenz in höhere Frequenzbereiche. Die Tremorintensität zeigte sich zudem abhängig vom Gangzyklus und der muskulären Belastung während des Gehens. Diese Beobachtungen legen nahe, dass es zu einer Interaktion zwischen dem orthostatischen Tremor und oszillatorischen, supraspinalen Lokomotionsarealen kommt und dass die periphere Manifestation des Tremors durch spinale Interneuron-Verschaltungen moduliert wird. Mittels einer multimodalen, klinisch-apparativen Ganguntersuchung wurden spatiotemporale Gangparameter bei Patienten mit orthostatischem Tremor erhoben, die mit einer altersgleichen, gesunden Kohorte verglichen wurde. Patienten mit orthostatischem Tremor zeigten ein breitbasiges Gangmuster mit erhöhter Gangvariabilität. Das Gangmuster verschlechterte sich beim langsamen Gehen und unter Augenschluss passend zu einer ataktischen Gangstörung mit sensorischen- und/oder zerebellären Defiziten. Eine weitere Aggravation in der kognitiven Dual Task-Bedingung offenbarte zudem motorisch-kognitive Defizite der Patienten. Somit scheint beim orthostatischen Tremor eine komplexe Netzwerkerkrankung mit einer spezifischen spino-zerebello-frontokortikalen Gangstörung vorzuliegen. Schließlich wurde in Folge einer kontinuierlichen Muskelsehnenvibrationsstimulation der unteren Extremitäten bei Patienten mit orthostatischem Tremor eine Reduktion der Tremorintensität und Körperschwankungen beobachtet. Bei bislang limitierten medikamentösen und invasiven Behandlungsmöglichkeiten bietet diese Beobachtung Hoffnung auf eine neue, nicht-invasive Therapieoption für Patienten mit orthostatischem Tremor.Primary orthostatic tremor is a rare disorder with high-frequency (13-18 Hz) leg muscle contractions during standing with relief of symptoms while sitting, walking, and lying. Recent studies found a specific ponto-cerebello-thalamo-cortical tremor network with persisting activity during lying. The aim of this dissertation was to answer following questions: 1) How does the tremor change in response to the transition from standing to walking? 2) Is orthostatic tremor associated with a specific gait disorder despite patients' sensation of symptom relief while walking? 3) Can the tremor be modulated through a non-invasive proprioceptive stimulation? In a first study, we examined the tremor of patients with orthostatic tremor during standing and walking conditions on a pressure-sensitive treadmill by means of surface electromyography of different leg muscles. We found that the tremor persisted during walking. Directly after gait initiation, the tremor frequency was shifted towards higher frequencies, but returned to the initial frequency after gait termination. While walking, the tremor was modulated in dependence of the gait cycle and individual exerted muscle forces. These observations point to a non-linear interference between the tremor and the oscillatory activity in supraspinal locomotor areas; furthermore, they indicate that the peripheral manifestation of the tremor is likely modulated by spinal interneuron connections. In a second study, we performed a multi-conditional, instrument-based gait assessment in patients with orthostatic tremor and age-matched healthy controls. Patients showed a broad-based walking pattern with increased gait variability with aggravation during slow walking modes and while walking with eyes closed. These gait alterations resemble an ataxic gait disorder indicative of sensory and/or cerebellar deficits. In addition, patients' walking performance deteriorated during a cognitive dual task paradigm pointing to a motor-cognitive dysfunction. Overall, the gait impairment in orthostatic tremor manifests in a specific spino-cerebello-frontocortical gait disorder. In a third study, we examined the effects of a proprioceptive leg muscle stimulation via muscle tendon vibration in patients with orthostatic tremor. We found that this stimulation yielded a reduction of tremor intensity and postural sway. In the light of currently limited pharmacological and invasive treatment options for orthostatic tremor, the observations of this study might pave the way for a new, non-invasive treatment option for patients

Reflection of individual typological properties in the tremorogram (Predicting the indicators of Rusalov’s test according to the indicators of the tremorogram)

Rationale for choosing. An increase in physiological tremor (Tr) in emotionally saturated situations is reflected not only in fiction, but also in scientific literature. In other words, tremors and emotional responses are interconnected. Purpose. To investigate the reflection of individual-typological properties in a tremorogram using V. M. Rusalov’s mathematical modeling. Material and methods. Tr was recorded using a linear transducer. Tr was recorded under postural load (arms extended forward). The sensor was alternately placed on the outstretched right and left arms in front of oneself, under conditions of “eyes open” (operative rest). The analysis of the tremorogram (TrG) files was carried out after the end of the study using the "Analist - 2" software according to the half - period analysis algorithm. To study the individual psychological characteristics of the personality, we used the method of determining the properties of the temperament by V.M. Rusalov. Each of the many indicators of Rusalov’s test selected in the analysis was considered as a target feature (Y-s), and the amplitudes and frequencies of TrG were considered as influencing variables (sets of X - s) and multiple linear regression equations of the form were built: The parameters of the amplitude and frequency of EEG rhythms were used as Xs. Own research. In multiple regression analysis of the influence of TrG indices of the right hand on the indices of Rusalov’s test, 12 statistically significant regression coefficients were determined, and 11 statistically significant regression coefficients for the left hand. After obtaining the diagnostic equations of multiple linear regression, describing the influence of TrG indicators on the indicators of Rusalov’s test, an attempt was made, using these equations, to obtain the indicators of Rusalov’s test, using the tremor indicators. On average, the% discrepancy between the determined and predicted indicators was 97.42% for the right hand, and 101.98 for the left. Conclusions. 1. With the use of diagnostic equation, it was possible to predict the indicators of psychological testing according to Rusalov’s test by the indicators of tremor of the right and left hands. 2. Influence of Rusalov’s test indicators on TrG indicators were less in modulus than the influence of TrG indicators on the indicators of Rusalov’s test, i.e. did not participate in the control of the mechanisms of TrG generation. 3. The results obtained indicate that tremor indicators contain information about the subject-activity and communicative aspects of temperament according to V. M. Rusalov