Quantification of hand tremor in the clinical neurological examination

Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson's disease motor symptoms

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor impairments such as tremor, bradykinesia, dyskinesia, and gait abnormalities. Current protocols assess PD symptoms during clinic visits and can be subjective. Patient diaries can help clinicians evaluate at-home symptoms, but can be incomplete or inaccurate. Therefore, researchers have developed in-home automated methods to monitor PD symptoms to enable data-driven PD diagnosis and management. We queried the US National Library of Medicine PubMed database to analyze the progression of the technologies and computational/machine learning methods used to monitor common motor PD symptoms. A sub-set of roughly 12,000 papers was reviewed that best characterized the machine learning and technology timelines that manifested from reviewing the literature. The technology used to monitor PD motor symptoms has advanced significantly in the past five decades. Early monitoring began with in-lab devices such as needle-based EMG, transitioned to in-lab accelerometers/gyroscopes, then to wearable accelerometers/gyroscopes, and finally to phone and mobile & web application-based in-home monitoring. Significant progress has also been made with respect to the use of machine learning algorithms to classify PD patients. Using data from different devices (e.g., video cameras, phone-based accelerometers), researchers have designed neural network and non-neural network-based machine learning algorithms to categorize PD patients across tremor, gait, bradykinesia, and dyskinesia. The five-decade co-evolution of technology and computational techniques used to monitor PD motor symptoms has driven significant progress that is enabling the shift from in-lab/clinic to in-home monitoring of PD symptoms.

Quantification of physiological kinetic tremor and its correlation with aging

Tremor is the most common movement disorder characterized by repetitive and stereotyped movements. The analysis of hand-drawing movements is commonly used in the evaluation of patients with tremor. The data collection conducted under kinetic conditions and while performing a voluntary movement highlights the kinetic tremor. Most investigations on tremor attempt to understand its relation to neuromuscular dysfunctions. Therefore, there is a lack of studies that aim to investigate the complex relation between the physiological tremor and aging, especially in kinetic conditions. In this context, the main motivation of this research was to generalize the results obtained in Almeida et al., a study that quantified age-related changes in the kinetic tremor of clinically healthy individuals. For this, a number of features extracted from tremor activity, obtained from digitized drawings of Archimedes' spirals, were analyzed. The analyses followed the sequence: Linearization of the Archimedes' spiral; Estimate of tremor activity; Data pre-processing; Feature extraction from the tremor activity; and Application of Linear Discriminant Analysis (LDA) technique as described in Almeida et al.. The generalization of the obtained results showed that the method based on LDA allows for a linear correlation between physiological kinetic tremor and aging.

Investigation of age-related changes in physiological kinetic tremor

Tremor is the most common movement disorder characterized by repetitive and stereotyped movements. Most investigations on tremor attempt to understand its relation to neuromuscular dysfunctions. Therefore, there is a lack of studies that aim to investigate the complex relation between the physiological tremor and aging, especially in kinetic conditions. In this context, the main motivation of this research was to quantify age-related changes in the kinetic tremor of clinically healthy individuals. For this, a number of features extracted from tremor activity, obtained from digitized drawings of Archimedes' spirals, were analyzed. In total, 59 subjects participated in the experiments. These individuals were divided into seven groups according to their ages and two types of analysis were carried out. First, the tremor activity of young and elderly adults was investigated by means of traditional features commonly used in tremor analysis, and secondly, linear discriminant analysis (LDA) was employed for the study of the correlation between age and tremor. The results showed significant statistical differences between the kinetic tremor activity of the young and elderly groups. Furthermore, it was found that LDA allowed for the estimate of a unique feature, so-called LDA-value, which showed to be linearly correlated with age.

Evaluation of an isometric and a position joystick in a target acquisition task for individuals with cerebral palsy

Individuals with cerebral palsy (CP) with upper limb disability have difficulty operating standard computer input devices such as, a mouse and a keyboard. The present study evaluated the performance of unimpaired individuals and those with CP in the use of a zero-order spring-centered position joystick and a zero-order isometric joystick when interacting with the computer. We hypothesize that the isometric device due to its stiff resistance would provide better control on cursor movement than the position joystick. The subjects acquired differently sized targets at different distances by positioning a cursor on the target. Performance with the position joystick was superior to that of the isometric joystick. The time to acquire the target was directly proportional to the cursor-target distance A, and indirectly proportional to the target size W. Subjects chose to move more slowly toward the smaller and closer targets and they increased speed for larger and more distant targets. The phase-plane diagram that plots values of the velocity profile of the cursor over its displacement revealed the presence of one large amplitude movement that accounts for the peak velocity of the cursor, and several submovements. Fitts' index of difficulty, log(e)(2W/A) was found to be a good predictor of the movement time in a cursor positioning task for both, unimpaired individuals and those with CP.

The application of video image processing to quantitative analysis of extremity tremor in humans

A new method for the detection and quantification of extremity tremor is described, based on video image processing. A single CCD camera recorded the movement of the extremity. A passive marker in the shape of a black annulus was placed on the forearm and the movement of the annulus analysed. The framestore digitised the video signal at a sample rate of 10 Hz. The time period of the movement analysis was delta t = 6.4 s. A total of 32 adults with alcoholism and 22 controls participated in this study. The movement of the extremity was recorded during the usual neurological test (sitting posture, feet together, upper extremities directly in front of subject) for both extremities. In this study, it was assumed that the probability density function f(d) of some variable D is characteristic of the tremor. This function is formed by a finite mixture of bivariate continuous distributions. The results suggest that f(d) characterises patients with alcoholism and distinguishes them from control subjects with only physiological tremor. The results demonstrate the capacity of the measuring system based on video imaging to quantifying motor impairments in clinical neurology.

Portable system for quantifying motor abnormalities in Parkinson's disease

In order to quantify motor disabilities in Parkinson's disease (PD), we designed a compact, portable, neurophysiological system based upon a personal computer to measure tremor, bradykinesia, and muscle tone. Tremor was detected by solid state accelerometers and translated into a digital signal. The system displayed the root mean square displacements and frequency distribution of the tremor in the horizontal and vertical planes, along with a reconstructed graphic image of the displacement. Bradykinesia was measured using a panel that detects release and depression of switches in response to auditory and visual signals; the system calculated subjects' reaction times and movement times in milliseconds. Tone at the elbow was measured by strapping the upper extremity to a lightweight low-friction cradle and then passively moving the cradle with an instrumented handle. Signals representing torque and arm angle were processed by the computer and displayed in real time on the screen with stiffness as a mean slope in Nm/degree. In clinical tests, quantitative measures of tremor, movement time and rigidity were significantly abnormal in PD patients compared to control subjects. We conclude that this system is a convenient and accurate method to quantitate important aspects of the parkinsonian syndrome, and may be applied to quantitate other movement disorders.

Quantification of motor function in toxicology

Disturbances of movement and other motor functions can result from exposure to toxicants and drugs. Sometimes, as with acute exposure to ethanol or solvents, these effects disappear when exposure ends. Other times, as with manganese, haloperidol, or chronic ethanol, motor disturbances are irreversible and may even lie undetected until after exposure has ended. Motor disturbances can take on many guises, including tremor, difficulty in positioning, fatigue, or rigidity. Techniques for measuring these different endpoints in primates will be addressed. One preparation that enables the simultaneous monitoring of positioning, tremor, and operant behavior in nonhuman primates is described, and tactics for obtaining spectral estimates of tremor from a positioning task are outlined. The spectra obtained from this preparation are reliable and valid: they are stable over a period of a year, they correspond to spectra obtained from accelerometers, and are altered by acute administration of ethanol or oxotremorine. These two drugs had opposite effects on tremor but affected bar positioning in a similar manner.

A new ambulatory monitoring system for tremor

We have described a fully portable tremor recording system which allows a patient to carry out his normal day's activities with minimal hindrance. Computer analysis of the recording has enabled the extent of the tremor over prolonged periods to be presented in a format which is easily understandable and which should be useful for the objective assessment of therapy.

A study of the muscle force waveform using a population stochastic model of skeletal muscle

A population stochastic model based on the differing properties and the independent activation of motor units is used to describe the production of force in the contracting skeletal muscle. Detailed force predictions of the model concerning a hand muscle are obtained by computer simulation. General features of the force signal are established analytically on the basis of the general properties of the neuromuscular system which the population model takes into account. The results show that the asynchronous activity of motor units and the distribution of their filtering and firing properties at various levels of muscle contraction are responsible, at least partially, for the main features of the muscle force waveform, including tremor.

Lumped and population stochastic models of skeletal muscle: implications and predictions

Lumped models of skeletal muscle have been assumed a) in the design of experiments and the interpretation of experimental findings, b) in theoretical studies. In this paper, a population model that takes into account the differing properties and separate (independent) activation of motor units is presented as the most appropriate for muscle. A realistic (for muscle) transformation, population leads to lumped model, resulting in the lumping of motor unit neural signals or system responses, is proposed. On this basis, the possibility of modelling muscle as a single system is examined; and the consequences of treating muscle as a lumped system, in experiments or theoretical studies, are discussed. Also, the advantages of lumping, in models of muscle, are reviewed. Predictions of a computer population model, together with actual recordings from a hand muscle, are used to confirm the results of the analysis.