Tremor is the most common movement disorder and differs from other disorders by its repetitive, stereotyped movements, with regular frequency and amplitude. The three most frequent pathological forms of it are the essential tremor (ET), the Parkinson's disease (PD) tremor, and the enhanced physiological tremor. The ET and PD tremor affect the older population mostly. Although there are cases of tremor reported since ancient times, there is currently no consensus about its causes or about its main differential characteristics. In this article, we present a review of the methods more frequently used in measurement and analysis of tremor and the difficulties encountered in the research for the identification of methodologies that allow a significant advance in the study of tremor.

Parkinson's disease (PD) presents several motor signs, including tremor and bradykinesia. However, these signs can also be found in other motor disorders and in neurologically healthy older adults. The incidence of bradykinesia in PD is relatively high in all stages of the disorder, even when compared to tremor. Thus, this research proposes an objective assessment of bradykinesia in patients with PD (G : 15 older adults with Parkinson's disease, 65.3 ± 9.1 years) and older adults (G: 12 healthy older adults, 60.1 ± 6.1 years). The severity of bradykinesia in the participants of G was assessed using the Unified Parkinson's Disease Rating Scale. Movement and muscular activity were detected by means of inertial (accelerometer, gyroscope, magnetometer) and electromyographic sensors while the participants performed wrist extension against gravity with the forearm on pronation. Mean and standard error of inertial and electromyographic signal parameters could discriminate PD patients from healthy older adults (p value<0.05). In discriminating patients with PD from healthy older adults, the mean sensitivity and specificity were respectively 86.67 and 83.33%. The discrimination between the groups, based on the objective evaluation of bradykinesia, may contribute to the accurate diagnosis of PD and to the monitoring of therapies to control parkinsonian bradykinesia, and opens the possibility for further comparative studies considering individuals suffering from other motor disorders.

BackgroundThe human body adopts a number of strategies to maintain an upright position. The analysis of the human balance allows for the understanding and identification of such strategies. The displacement of the centre of pressure (COP) is a measure that has been successfully employed in studies regarding the postural control. Most of these investigations are related to the analysis of individuals suffering from neuromuscular disorders. Recent studies have shown that the elderly population is growing very fast in many countries all over the world, and therefore, researches that try to understand changes in this group are required. In this context, this study proposes the analysis of the postural control, measured by the displacement of the COP, in groups of young and elderly adults.MethodsIn total 59 subjects participated of this study. They were divided into seven groups according to their age. The displacement of the COP was collected for each subject standing on a force plate. Two experimental conditions, of 30 seconds each, were investigated: opened eyes and closed eyes. Traditional and recent digital signal processing tools were employed for feature computation from the displacement of the COP. Statistical analyses were carried out in order to identify significant differences between the features computed from the distinct groups that could allow for their discrimination.ResultsOur results showed that Linear Discrimination Analysis (LDA), which is one of the most popular feature extraction and classifier design techniques, could be successfully employed as a linear transformation, based on the linear combination of standard features for COP analysis, capable of estimating a unique feature, so-called LDA-value, from which it was possible to discriminate the investigated groups and show a high correlation between this feature and age.ConclusionThese results show that the analysis of features computed from the displacement of the COP are of great importance in studies trying to understand the ageing process. In particular, the LDA-value showed to be an adequate feature for assessment of changes in the postural control which can be related to functional changes that occur over the ageing.

Although technology and computation power have become more and more present in our daily lives, we have yet to see the same tendency in robotics applied to health care. In this work we focused on the study of four distinct applications of robotic technology to health care, named Robotic Assisted Surgery, Robotics in Rehabilitation, Prosthetics and Companion Robotic Systems. We identified the main roadblocks that are limiting the progress of such applications by an extensive examination of recent reports. Based on the limitations of the practical use of current robotic technology for health care we proposed a general modularization approach for the conception and implementation of specific robotic devices. The main conclusions of this review are: (i) There is a clear need of the adaptation of robotic technology (closed loop) to the user, so that robotics can be widely accepted and used in the context of heath care; (ii) For all studied robotic technologies cost is still prohibitive and limits their wide use. The reduction of costs influences technology acceptability, thus innovation by using cheaper computer systems and sensors are relevant and should be taken into account in the implementation of robotic systems.

BackgroundOver the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson’s disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy.MethodsIn this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon’s map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification.ResultsThe results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively.ConclusionsThis research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.