A novel computer-based technique for the assessment of tremor in Parkinson's disease

Writing tremor in Parkinson's disease: frequency and associated clinical features

Action tremor in Parkinson's disease may present in up to 46% of patients, either as postural or kinetic tremor. How action tremor may affect handwriting has been the object of some investigations; however, clinical features of writing tremor in Parkinson's disease are still not well-characterised. One hundred consecutive patients with idiopathic Parkinson's disease were included in the study. Demographic and clinical data were collected through a standardized questionnaire. Patients were assessed for the presence of rest, action and writing tremor in on condition. The effect of a standardised sensory trick (gently touching the wrist of the upper limb manifesting tremor with the contralateral hand) was also investigated in all patients with action tremor. Writing tremor was found in 10% of patients (26% of patients with postural/kinetic tremor, either alone or in combination with rest tremor). Severity of writing tremor did not correlated with that of the other tremor variants and to the other clinical variables. Writing tremor was task-specific in 4/10 patients, no task-specific in 6/10. Sensory trick was effective on writing tremor in two patients but did not improve action tremor in any of the study patients. Results showed that writing tremor in Parkinson's disease is less common than other tremor variants, may be associated with other forms of action tremor, and may sometimes have dystonic features, including task-specificity and sensitivity to sensory trick.

Strain Gauge Measuring System for Subsensory Micromotions Analysis as an Element of a Hybrid Human-Machine Interface

The human central nervous system is the integrative basis for the functioning of the organism. The basis of such integration is provided by the fact that the same neurons are involved in various sets of sensory, cognitive, and motor functions. Therefore, the analysis of one set of integrative system components makes it possible to draw conclusions about the state and efficiency of the other components. Thus, to evaluate a person's cognitive properties, we can assess their involuntary motor acts, i.e., a person's subsensory reactions. To measure the parameters of involuntary motor acts, we have developed a strain gauge measuring system. This system provides measurement and estimation of the parameters of involuntary movements against the background of voluntary isometric efforts. The article presents the architecture of the system and shows the organization of the primary signal processing in analog form, in particular the separation of the signal taken from the strain-gauge sensor into frequency and smoothly varying components by averaging and subtracting the analog signals. This transfer to analog form simplifies the implementation of the digital part of the measuring system and allowed for minimizing the response time of the system while displaying the isometric forces in the visual feedback channel. The article describes the realization of the system elements and shows the results of its experimental research.

Testing of Motor Coordination in Degenerative Neurological Diseases

Parkinson’s disease (PD) is a progressive movement disorder caused by the death of dopamine-producing cells in the midbrain. PD is the most prevalent movement disorder of the central nervous system and affects more than 6.3 million people in the world. The changes in the motor functions of patients are not easy to be clearly and on-time observed by the clinicians and to make the most well-informed decisions for the treatment. The aim of this paper is the monitoring PD by designing, developing, and evaluating a prototype mobile App using a pressure pen, which collects quantitative and objective information about PD patients, thus allowing clinicians to understand better and make assumptions about the severity and the stage of Parkinson’s disease. This study presents a dynamic spiral test that can only be performed with tablet and pen pressure. Furthermore, the handwriting samples by PD patients and healthy controls individuals are collected by a computerized system, and the measurements of Spiral Deviation, Total Time, and Pen Pressure are processed. The results showed an accurate evaluation of the stage of Parkinson’s disease. Thus, the clinician may use the proposed PD telemonitoring system as a screening test, storing the history of all the patient’s measurements.

Parkinson’s disease diagnosis using convolutional neural networks and figure-copying tasks

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that causes abnormal movements and an array of other symptoms. An accurate PD diagnosis can be a challenging task as the signs and symptoms, particularly at an early stage, can be similar to other medical conditions or the physiological changes of normal ageing. This work aims to contribute to the PD diagnosis process by using a convolutional neural network, a type of deep neural network architecture, to differentiate between healthy controls and PD patients. Our approach focuses on discovering deviations in patient’s movements with the use of drawing tasks. In addition, this work explores which of two drawing tasks, wire cube or spiral pentagon, are more effective in the discrimination process. With $$93.5\%$$ 93.5 % accuracy, our convolutional classifier, trained with images of the pentagon drawing task and augmentation techniques, can be used as an objective method to discriminate PD from healthy controls. Our compact model has the potential to be developed into an offline real-time automated single-task diagnostic tool, which can be easily deployed within a clinical setting.

Tensometric tremorography in high-precision medical diagnostic systems

BACKGROUND

The objective of the study was to develop a system for the precision diagnostics of pathologies of motor brain regions based on tensometric measurement and to explore its diagnostic capabilities.

MATERIALS AND METHODS

Tremor is a syndrome that indicates the abnormal state of the central nervous system, primarily in the motor brain regions. Analysis of tremor parameters provides significant information about the changes in the body motion control and can be used as an objective index of the central nervous system state. Existing methods are aimed at the analysis of visible tremor based on the use of different sensors. We suggest an alternative approach based on the use of a tensometric system performing tremor measurements when the tremor appears on the background of voluntary isometric efforts. The key advantage of our approach is that it allows to determine the tremor before its visible manifestation. In the article, we describe hardware implementation of our tremor analysis system.

RESULTS

In the article, we represent the new methodology and the original equipment based on the control of isometric effort. Isometric effort formed by a patient is controlled with the use of a feedback system on the patient's monitor. We evaluated the performance of our equipment with more than 400 healthy volunteers and patients with various pathologies of the central nervous system motor regions, and the results of the investigations, allowing to identify tremor parameters typical for parkinsonism, are represented in our article.

CONCLUSION

Testing of the system confirmed its high diagnostic validity and reliability, high sensitivity, simplicity and high speed of information processing. The approach based on tensometric measurements is very promising for the diagnostics of Parkinson disease and dysfunctions of a central nervous system.

Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis

Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS.

Validity and reliability of a new tool to evaluate handwriting difficulties in Parkinson's disease

BACKGROUND

Handwriting in Parkinson's disease (PD) features specific abnormalities which are difficult to assess in clinical practice since no specific tool for evaluation of spontaneous movement is currently available.

OBJECTIVE

This study aims to validate the 'Systematic Screening of Handwriting Difficulties' (SOS-test) in patients with PD.

METHODS

Handwriting performance of 87 patients and 26 healthy age-matched controls was examined using the SOS-test. Sixty-seven patients were tested a second time within a period of one month. Participants were asked to copy as much as possible of a text within 5 minutes with the instruction to write as neatly and quickly as in daily life. Writing speed (letters in 5 minutes), size (mm) and quality of handwriting were compared. Correlation analysis was performed between SOS outcomes and other fine motor skill measurements and disease characteristics. Intrarater, interrater and test-retest reliability were assessed using the intraclass correlation coefficient (ICC) and Spearman correlation coefficient.

RESULTS

Patients with PD had a smaller (p = 0.043) and slower (p<0.001) handwriting and showed worse writing quality (p = 0.031) compared to controls. The outcomes of the SOS-test significantly correlated with fine motor skill performance and disease duration and severity. Furthermore, the test showed excellent intrarater, interrater and test-retest reliability (ICC > 0.769 for both groups).

CONCLUSION

The SOS-test is a short and effective tool to detect handwriting problems in PD with excellent reliability. It can therefore be recommended as a clinical instrument for standardized screening of handwriting deficits in PD.

Task-specific kinetic finger tremor affects the performance of carrom players

We aimed to determine the effect of task-specific kinetic finger tremor, as indexed by surface electromyography (EMG), on the accuracy of a carrom stroke. Surface EMG of extensor digitorum communis muscle of the playing arm was recorded during rest, isometric contraction and stroke execution in 17 male carrom players with clinically observed finger tremor and 18 skill- and age-matched controls. Log-transformed power spectral densities (LogPSDs) of surface EMG activity (signifying tremor severity) at a 1-s pre-execution period correlated with angular error of the stroke. LogPSDs in 4-10 Hz range were higher in players with tremor than controls during pre-execution (P < 0.001), but not during the resting state (P = 0.067). Pre-execution tremor amplitude correlated with angular deviation (r = 0.45, P = 0.007). For the first time, we document a task-specific kinetic finger tremor in carrom players. This finger tremor during the immediate pre-execution phase appears to be a significant determinant of stroke accuracy.

Using a smart phone as a standalone platform for detection and monitoring of pathological tremors

Introduction: Smart phones are becoming ubiquitous and their computing capabilities are ever increasing. Consequently, more attention is geared toward their potential use in research and medical settings. For instance, their built-in hardware can provide quantitative data for different movements. Therefore, the goal of the current study was to evaluate the capabilities of a standalone smart phone platform to characterize tremor. Results: Algorithms for tremor recording and online analysis can be implemented within a smart phone. The smart phone provides reliable time- and frequency-domain tremor characteristics. The smart phone can also provide medically relevant tremor assessments. Discussion: Smart phones have the potential to provide researchers and clinicians with quantitative short- and long-term tremor assessments that are currently not easily available. Methods: A smart phone application for tremor quantification and online analysis was developed. Then, smart phone results were compared to those obtained simultaneously with a laboratory accelerometer. Finally, results from the smart phone were compared to clinical tremor assessments.

Motor signs in the prodromal phase of Parkinson's disease

Relatively subtle deterioration of the motor system likely occurs well before the patient meets established motor criteria for a clinical diagnosis of Parkinson's disease; ie, the occurrence of at least 2 of the cardinal motor deficits: bradykinesia, rigidity, tremor, and/or postural instability. Powerful compensatory mechanisms may mask these clinical symptoms and make them difficult to identify and evaluate in the earliest stages of the illness. This review summarizes our current knowledge of motor signs that are thought to occur in the prodromal phase of Parkinson's disease and suggests how motor assessment batteries could be designed to detect these subclinical motor deficits with a high degree of accuracy and sensitivity.

Validation of a home environment test battery for supporting assessments in advanced Parkinson's disease

Test sequences in a test battery for Parkinson's disease patients, consisting of self-assessments and motor tests, were carried out repeatedly in a telemedicine setting, during week-long test periods and results were summarized in an 'overall score'. 35 patients in stable and fluctuating conditions (15 age- and gender-matched pairs) used the test battery for 1 week, and were then assessed with UPDRS and PDQ-39. This procedure was repeated 1 week later, without treatment changes. Reliability was assessed by intraclass correlation coefficients and Cronbach's alpha. Convergent validity was assessed by Spearman rank correlations and known-groups' validity, by the Mann-Whitney test. According to anonymous usability questionnaires, the patients could easily complete the tasks. Median compliance (93%) and test-retest reliability (0.88) were good. The correlations between overall score and total UPDRS (-0.64) and PDQ-39 (-0.72) were adequate. Median overall score was 18% better in the stable compared to the fluctuating group (p = 0.0014).

Computer-based assessment of movement difficulties in Parkinson's disease

The prevalence of Parkinson's disease (PD) is increasing due to an ageing population. It is an unpredictable disease which requires regular assessment and monitoring. Current techniques used to assess PD are subjective. Clinicians observe movements made by a patient and subsequently rate the level of severity of, for example tremor or slowness of movement. Within this work, we have developed and evaluated a prototype computer-based assessment tool capable of collecting information on the movement difficulties present in PD. Twenty participants took part in an assessment of the tool, 10 of whom were diagnosed with PD and 10 were without the disease. Following the usage of the tool, it was found that there was a significant difference (p = 0.038) in the speed of movement between the two groups. We envisage that this tool could have the potential to enable more objective clinical conclusions to be made.

Assessing manual pursuit tracking in Parkinson's disease via linear dynamical systems

Quantitative assessment of motor performance is important for diseases of motor control, such as Parkinson's disease (PD). Manual tracking tasks are well suited for motor assessment, as they can be performed concomitantly with brain mapping techniques. Here we propose utilizing second-order linear dynamical systems to assess manual pursuit tracking performance. With the desired trajectory as the input, and the subject's actual motor response as the output, a linear model characterized by natural frequency and damping ratio is identified for each subject. We applied this method to 10 PD subjects (on and off L: -dopa medication) and 10 normal subjects performing a multi-frequency sinusoidal tracking task. Model parameters were more sensitive than overall tracking errors in determining significant differences between groups. The effect of L: -dopa medication was to reduce the damping ratio and make the range in natural frequency across individuals approach that of normal subjects. We interpret the changes in damping ratio and natural frequency as possibly related to suppression of compensatory cerebellar activity and/or improvement of motor program selection, and the changes in natural frequency as an implicit strategy to maintain settling time in the face of reduce damping ratio. Our results suggest that simple linear dynamical system models can be a powerful method to assess tracking performance in Parkinson's disease because of the additional insight they can provide into neurological processes.

Rapid tremor frequency assessment with the iPhone accelerometer

The physician is often seeking more efficient ways of performing patient assessments. Currently, measuring tremor frequency requires expensive and bulky equipment. We propose the use of the in-built accelerometer of the iPhone via the iSeismo application for rapid measurement of tremor frequency. We use this device in a series of 7 different tremor cases, and show that the frequency measurements on the iSeismo graph closely match the more sophisticated EMG analysis during tremor. This is a preliminary confirmation of the usefulness of this device in the clinical setting for quick assessment of the dominant frequency component in a variety of tremors.

A new computer method for assessing drawing impairment in Parkinson's disease

A test battery, consisting of self-assessments and motor tests (tapping and spiral drawing tasks) was used on 9482 test occasions by 62 patients with advanced Parkinson's disease (PD) in a telemedicine setting. On each test occasion, three Archimedes spirals were traced. A new computer method, using wavelet transforms and principal component analysis processed the spiral drawings to generate a spiral score. In a web interface, two PD specialists rated drawing impairment in spiral drawings from three random test occasions per patient, using a modification of the Bain & Findley 10-category scale. A standardised manual rating was defined as the mean of the two raters' assessments. Bland-Altman analysis was used to evaluate agreement between the spiral score and the standardised manual rating. Another selection of spiral drawings was used to estimate the Spearman rank correlations between the raters (r=0.87), and between the mean rating and the spiral score (r=0.89). The 95% confidence interval for the method's prediction errors was +/-1.5 scale units, which was similar to the differences between the human raters. In conclusion, the method could assess PD-related drawing impairments well comparable to trained raters.

A home environment test battery for status assessment in patients with advanced Parkinson's disease

A test battery for assessing patient state in advanced Parkinson's disease, consisting of self-assessments and motor tests, was constructed and implemented on a hand computer with touch screen in a telemedicine setting. The aim of this work was to construct an assessment device, applicable during motor fluctuations in the patient's home environment. Selection of self-assessment questions was based on questions from an e-diary, previously used in a clinical trial. Both un-cued and cued tapping tests and spiral drawing tests were designed for capturing upper limb stiffnes, slowness and involuntary movements. The patient interface gave an audible signal at scheduled response times and was locked otherwise. Data messages in an XML-format were sent from the hand unit to a central server for storage, processing and presentation. In tapping tests, speed and accuracy were calculated and in spiral tests, standard deviation of frequency filtered radial drawing velocity was calculated. An overall test score, combining repeated assessments of the different test items during a test period, was defined based on principal component analysis and linear regression. An evaluation with two pilot patients before and after receiving new types of treatments was performed. Compliance and usability was assessed in a clinical trial (65 patients with advanced Parkinson's disease) and correlations between different test items and internal consistency were investigated. The test battery could detect treatment effect in the two pilot patients, both in self-assessments, tapping tests' results and spiral scores. It had good patient compliance and acceptable usability according to nine nurses. Correlation analysis showed that tapping results provided different information as compared to diary responses. Internal consistency of the test battery was good and learning effects in the tapping tests were small.