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There are 2 main reasons why pig gait is analysed. First, assessment of a pig's health and welfare is major reason for gait analysis. Also, the pig, as a large animal model, has become important in biomedical research, especially in preclinical testing of therapeutics. Gait is an essential part of pig movement and its analysis is of great interest, especially when following the phenotype and the effectivity of treatment in pig models for movement and neurological disorders. The aim of this state-of-the-art review is 3-fold: (1) to present and summarize the current instrument base used in pig gait assessment, (2) to point out promising technologies for pig gait analysis, and (3) to outline the suitability of technology for pig gait analysis. The review encompasses 27 studies in total. We included papers published since 2010 and classified them according to which type of measurement instrument was used: 2D camera systems, 3D camera systems, force plates and pressure sensitive mats. In each category we reviewed the data acquisition systems, utilized signals and gait parameters used. An analysis of the literature showed that video-based systems and pressure sensitive mats were the most frequently used. The utilization of 3D camera systems was less common. Force plates were only used occasionally. In conclusion, despite growing interest in using inertial sensor units in movement analysis, they were missing in pig gait analysis. Along with the progress in instrumentation and its ability to produce a huge amount of information, simpler and more user-friendly tools should be developed to provide easy interpretation of the data captured by pig practitioners in the pig industry, or by scientists.

Idiopathic rapid eye movement sleep behaviour (iRBD) is considered as a risk factor for Parkinson's disease (PD) development. Evaluation of repetitive movements with finger tapping, which serves as a principal task to measure the extent of bradykinesia in PD, may undercover potential PD patients. The aim of this study was to explore whether finger tapping abnormalities, evaluated with a 3D motion capture system, are already present in RBD patients.Finger tapping data was acquired using a contactless 3D motion capture system from 40 RBD subjects and compared to 25 de-novo PD patients and 25 healthy controls. Objective assessment of amplitude decrement, maximum opening velocity and their combination representing finger tapping decrement was performed in the sequence of the first ten tapping movements. The association between instrumental finger tapping data and semi-quantitative clinical evaluation was analyzed.While significant differences between PD and controls were found for all investigated finger tapping measures (p 0.002), RBD differed from controls in finger tapping amplitude (p = 0.004) and velocity (p = 0.007) decrement but not in maximal opening velocity. A significant relationship between the motor score from the Movement Disorders Society - Unified Parkinson's Disease Rating Scale and finger tapping decrement was shown for both patient groups, ie RBD (r = 0.36, p = 0.02) and PD (r = 0.60, p = 0.002).In our group of RBD patients we demonstrated amplitude decrement of repetitive movements, which may correspond with prodromal bradykinesia. Our findings suggest instrumental analysis of finger tapping abnormalities as a potential novel clinical marker reflecting subclinical motor disturbances in RBD.

OBJECTIVES Hyperechogenicity of the substantia nigra (SN) and abnormal dopamine transporter-single-photon emission computed tomography (DAT-SPECT) are biomarkers commonly used in the assessment of prodromal synucleinopathy. Our goals were as follows: (1) to compare echogenicity of SN in idiopathic rapid eye movement (REM) behavior disorder (iRBD), Parkinson's disease (PD) without RBD (PD-noRBD), PD with RBD (PD + RBD), and control subjects; and (2) to examine association between SN degeneration assessed by DAT-SPECT and SN echogenicity. PATIENTS/METHODS A total of 61 subjects with confirmed iRBD were examined using Movement Disorders Society-unified PD rating scale (MDS-UPDRS), TCS (transcranial sonography) and DAT-SPECT. The results were compared with 44 patients with PD (25% PD + RBD) and with 120 age-matched healthy subjects. RESULTS AND CONCLUSION The abnormal SN area was found in 75.5% PD, 23% iRBD and 7.3% controls. Median SN echogenicity area in PD (0.27 ± 0.22 cm2) was higher compared to iRBD (0.07 ± 0.07 cm2; p

The Timed Up & Go (TUG) test is a simple test for gait and balance that requires no special equipment and can be part of a routine clinical examination. Combined with the development of motion capture technologies, the possibilities of assessing individual TUG sub-components (i.e. sit-to-stand, gait, turn, turn-to-sit) are increasing. The clinical evaluation of an instrumented TUG requires reliable values. We analysed the intra-session repeatability of the iTUG sit-to-stand, gait and turn parameters in three conditions: (1) single, (2) cognitive dual-tasks, and (3) manual dual-tasks in older adults and Parkinson's disease (PD) patients. The repeatability coefficient (RC) was calculated for each of the 18 parameters. The repeatability varied across subject groups, the performed tasks, and the TUG subcomponent. The gait subcomponent had 6 non-repeatable spatio-temporal parameters and 2 non-repeatable parameters for the arm swing. The parameters of the turn subcomponent can be considered as non-repeatable in both groups under the manual dual-task condition and in HC under the single-task condition. When comparing PD to HC, the repeatability of the majority of the single-task parameters was higher in PD whereas lower under dual-tasks. In PD, the major part of gait parameters had a higher repeatability under single-tasks than dual-tasks. In contrast, HC exhibited better repeatability of dual-tasks than single-tasks. Repeatability can be used to assist researchers and clinicians to select adequate parameters with respect to the purpose of motion assessment.

Deep brain stimulation (DBS) is an internationally accepted form of treatment option for selected patients with Parkinson’s disease and dystonia. Intraoperative extracellular microelectrode recordings (MER) are considered as the standard electrophysiological method for the precise positioning of the DBS electrode into the target brain structure. Pre-processing of MERs is a key phase in clinical analysis, with intraoperative microelectrode recordings being prone to several artifact groups (up to 25 %). The aim of this methodological article is to provide a convolutional neural network (CNN) processing pipeline for the detection of artifacts in an MER. We applied continuous wavelet transform (CWT) to generate an over-complete time–frequency representation. We demonstrated that when attempting to find artifacts in an MER, the new CNN + CWT provides a high level of accuracy (ACC = 88.1 %), identifies individual classes of artifacts (ACC = 75.3 %) and also offers artifact time onset detail, which can lead to a reduction in false positives/negatives. In summary, the presented methodology is capable of identifying and removing various artifacts in a comprehensive database of MER and represents a substantial improvement over the existing methodology. We believe that this approach will assist in the proposal of interesting clinical hypotheses and will have neurologically relevant effects.

Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI.

Background Deep brain stimulation (DBS) is emerging as a viable treatment option for selected patients with dystonia. Intraoperative extracellular microelectrode recordings (MER) are considered as the standard electrophysiological method for the precise positioning of the DBS electrode into the target brain structure. Accurate targeting of the permanent stimulation electrode into the Globus Pallidus internus (GPi) is key to positive long-term effects. The suitability of the location is peroperatively assessed by microelectrodes that register single-unit neuronal activity. The aim of this article is to analyse electrophysiological recordings of patient's neuronal activity with a focus on the identification of markers relevant to the patient's clinical state. Methods In this study, 13 patients chronically treated with double-sided DBS GPi were examined with a microrecording. The signal (24 kHz) processing, included bandpass filtering (0.5–5 kHz), automated detection of artefacts and feature extraction. Pre-processed signals were analysed by means of statistical learning. Results The results show that the GPi was distinguished from its vicinity with p Conclusion This paper demonstrates the quantitative relationship between electrophysiological findings and the clinical effects of pallidal stimulation in dystonia and suggested objectification predictors of the effectiveness of this therapy.

Turning is an essential part of human movement. Turning manoeuvres are affected by age, neurological disorders, or frailty. Analyses of the walking turn and its alterations could provide valuable information about functional independence. Most studies involving wearable sensors quantify the turn by descriptive statistical values such as the mean or maximum of the signal. Along with growing interest in walking turn analysis, new parameters should be proposed. From statistics we adapted a parameter, referred to as waveform skewness, that describes the shape of the 180 ° turn signal. This parameter is then compared to established ones and an intraclass-correlation is calculated. The mutual relationship between the proposed parameter and established ones is investigated via correlation. In addition, the effect of different circumstances (temporal alignment, signal scaling and time shift) to the proposed parameter is quantified. Waveform skewness showed a moderate intra-class correlation and a high correlation with the signal peak value. The results showed that waveform skewness is not sensitive to the time shift but is sensitive to signal scaling and temporal alignment. Comparing the waveform skewness between the two subject groups revealed significant differences between Parkinson disease patients and the control group. Quantitative assessment of the 180 ° turn may allow for more objective and sensitive determinations of movement disorders and pathologies.

Deep brain stimulation of the globus pallidus internus is an efective symptomatic treatment for pharmacoresistant dystonic syndromes, where pathophysiological mechanisms of action are not yet fully understood. The aim of this review article is to provide an overview of the state-of-the-art approaches for processing of microelectrode recordings in dystonia; in order to define biomarkers to identify patients who will benefit from the clinical deep brain stimulation. For this purpose, the essential elements of microelectrode processing are examined. Next, we investigate a real example of spike sorting processing in this field. Herein, we describe baseline elements of microrecordings processing including data collection, preprocessing phase, features computation, spike detection and sorting and finally, advanced spike train data analysis. This study will help readers acquire the necessary information about these elements and their associated techniques. Thus, this study is supposed to assist during identification and proposal of interesting clinical hypotheses in the field of single unit neuronal recordings in dystonia.

The Timed Up & Go test (TUG) is functional test and is a part of routine clinical examinations. The instrumented Timed Up & Go test enables its segmentation to sub-tasks: sit-to-stand, walking forward, turning, walking back, stand-to-sit, and consequently the computation of task-specific parameters and sub-tasks separately. However, there are no data on whether walking forward parameters differ from the walking back parameters. This study tested the differences between walking forward and walking back in the TUG extended to 10 m for 17 spatio-temporal gait parameters. All parameters were obtained from a GAITRite® pressure sensitive walkway (CIR Systems, Inc.). The differences were assessed for healthy controls and Parkinson's disease (PD) patients. None of investigated parameters exhibited a difference between both gait subtasks for healthy subjects group. Five parameters of interest, namely velocity, step length, stride length, stride velocity, and the proportion of the double support phase with respect to gait cycle duration, showed a statistically significant difference between gait for walking forward and walking back in PD patients. Therefore, we recommend a separate assessment for walking forward and walking back rather than averaging both gaits together.

Neuromelanin (NM) is a black pigment located in the brain in substantia nigra pars compacta (SN) and locus coeruleus. Its loss is directly connected to the loss of nerve cells in this part of the brain, which plays a role in Parkinson’s Disease. Magnetic resonance imaging (MRI) is an ideal tool to monitor the amount of NM in the brain in vivo. The aim of the study was the development of tools and methodology for the quantification of NM in a special neuromelanin-sensitive MRI images. The first approach was done by creating regions of interest, corresponding to the anatomical position of SN based on an anatomical atlas and determining signal intensity threshold. By linking the anatomical and signal intensity information, we were able to segment the SN. As a second approach, the neural network U-Net was used for the segmentation of SN. Subsequently, the volume characterizing the amount of NM in the SN region was calculated. To verify the method and the assumptions, data available from various patient groups were correlated. The main benefit of this approach is the observer-independency of quantification and facilitation of the image processing process and subsequent quantification compared to the manual approach. It is ideal for automatic processing many image sets in one batch.

Gait is an essential movement and has been shown to be a relevant measure for differentiating gait pathologies and neurological conditions in humans as well as in animals. Inertial measurement units have been suggested as a promising tool for gait analysis. Gait analysis performed in pre-clinical animal models can improve the conversional reliability of preclinical research. Large animal models can confirm and augment results achieved in rodents prior to adaptation to humans. Because pigs are of similar body size to humans and their brains are more like humans than rodent brain, pigs are a more direct assessment of dosing in a preclinical model. Pig gait analysis is used to characterise the pathologies of motor control and to evaluate the effectiveness of treatments performed previously in clinical settings. Nowadays, there is no information on the reliability of large animal model gait signals, namely pig gait signals. This paper presents the pilot analysis of gait angular velocity and acceleration provided by inertial sensors placed on the front shoulders and tests them for intra-individual reliability. An intra-class correlation was employed to analyse inertial sensor signals from three healthy pigs. Most of tested pigs performed with good reliability for roll and pitch angular velocity, and vertical and medio-lateral acceleration. Therefore, we can recommend these signals for the basis in of continuous signal analysis.

The Timed Up and Go test is a well-known clinical test for assessing of mobility and fall risk. It has been shown that the IMU which use an accelerometer and gyroscope are capable of analysing the quantitative parameters of the sit-to-stand transition.Which signals obtained by the inertial sensors are suitable for continuous Timed UpGo test sit-to-stand transition analysis?In the study we included 29 older adult volunteers and 31 de-novo Parkinson disease (PD) patients. All subjects performed an instrumented extended TUG wearing a gyro-accelerometer. The sit-to-stand transition was detected from an angular velocity signal. The sit-to-stand signal pattern within the subject group was analyzed via an intra-class correlation between curves. Inter-subjects' variability was visualized using prediction bands.The angular velocity about the pitch axis exhibited the best signal match across subjects in both groups (0.50ICC0.75). When analysing acceleration, the acceleration along the antero-posterior axis showed moderate inter-subjects signal pattern match (0.50ICC0.75) in the reference group. The analysis of other signals revealed a poor signal pattern in both subject groups.For optimal interpretation of the analysis of continuous curves, the signal pattern must be considered. Also, the inter-subject variability along this pattern can be informative and useful.

In this work we report on the implementation of methods for data processing signals from microelectrode arrays (MEA) and the application of these methods for signals originated from two types of MEAs to detect putative neurons and sort them into subpopulations. We recorded electrical signals from firing neurons using titanium nitride (TiN) and boron doped diamond (BDD) MEAs. In previous research, we have shown that these methods have the capacity to detect neurons using commercially-available TiN-MEAs. We have managed to cultivate and record hippocampal neurons for the first time using a newly developed custom-made multichannel BDD-MEA with 20 recording sites. We have analysed the signals with the algorithms developed and employed them to inspect firing bursts and enable spike sorting. We did not observe any significant difference between BDD- and TiN-MEAs over the parameters, which estimated spike shape variability per each detected neuron. This result supports the hypothesis that we have detected real neurons, rather than noise, in the BDD-MEA signal. BDD materials with suitable mechanical, electrical and biocompatibility properties have a large potential in novel therapies for treatments of neural pathologies, such as deep brain stimulation in Parkinson’s disease.

Background Nowadays, the most widely used types of wearable sensors in gait analysis are inertial sensors. The aim of the study was to assess the agreement between two different systems for measuring gait parameters (inertial sensor vs. electronic walkway) on healthy control subjects (HC) and patients with Parkinson’s disease (PD). Methods Forty healthy volunteers (26 men, 14 women, mean age 58.7 ± 7.7 years) participated in the study and 24 PD patients (19 men, five women, mean age 62.7 ± 9.8 years). Each participant walked across an electronic walkway, GAITRite, with embedded pressure sensors at their preferred walking speed. Concurrently a G-Walk sensor was attached with a semi-elastic belt to the L5 spinal segment of the subject. Walking speed, cadence, stride duration, stride length, stance, swing, single support and double support phase values were compared between both systems. Results The Passing-Bablock regression slope line manifested the values closest to 1.00 for cadence and stride duration (0.99 ≤ 1.00) in both groups. The slope of other parameters varied between 0.26 (double support duration in PD) and 1.74 (duration of single support for HC). The mean square error confirmed the best fit of the regression line for speed, stride duration and stride length. The y-intercepts showed higher systematic error in PD than HC for speed, stance, swing, and single support phases. Conclusions The final results of this study indicate that the G-Walk system can be used for evaluating the gait characteristics of the healthy subjects as well as the PD patients. However, the duration of the gait cycle phases should be used with caution due to the presence of a systematic error.

SUMMARYGiven the advanced breakthroughs in the field of supportive robotic technologies, interest in the integration of the human body and a robot into a single system has rapidly increased. The aim of this work is to provide an overview of empowering lower limbs exoskeletons. Along with lower exoskeleton limbs, their unique design concepts, operator–exoskeleton interactions and control strategies are described. Although many problems have been solved in recent development, many challenges remain. Especially in the context of infantry soldiers, fire fighters and rescuers, the challenges of empowering exoskeletons are discussed, and improvements are outlined and described. This study is not only a summary of the current state, but also points to weaknesses of empowering lower limbs exoskeletons and outlines possible improvements.

Disorders of gait seriously affect the functional state and quality of life of patients with Parkinson’s disease (PD). Impaired brain function underlies disorders of movement control in PD, however functional brain imaging with magnetic resonance (fMRI) is not feasible during gait. Near-Infrared Spectroscopy (NIRS) is a portable imaging method for measuring brain activity. It uses low-energy optical radiation to detect local changes of (de)oxyhemoglobin concentration in the cerebral cortex, like a fMRI. We included 8 patients with advanced PD chronically treated with DBS STN. Brain activity was recorded with the NIRSport. Gait was examined in 10 cycles, during which the active and resting phases alternated. Changes in oxyhemoglobin concentration were calculated from the native NIRS signal using a modified transformation of the Lambert-Beer Law. The signals were filtered in the 0.015–0.3 Hz band and the least-squares algorithm was fitted with the HRF function for each cycle separately, from which the median was finally calculated. The activity of the motor cortex was significantly higher during gait in the OFF compared to ON state (p = 0.02). In contrast, in other regions no differences were found. A higher motor cortex activity shown in the DBS OFF compared to ON state may reflect the impairment of gait control in PD. In general terms, the present study demonstrates the potential utility of the NIRS method in detecting functional changes of the brain during gait in patients with PD.

Head tremor is a common clinical manifestation in essential tremor (ET) and can also occur as dystonic tremor (DT) in cervical dystonia. The clinical differentiation of head tremor due to ET and DT is not easy. Therefore, we developed instrumental methods using an accelerometer and an optical motion capture system to precisely measure and analyze head and hand tremor, and for distinguishing between ET and DT. Head tremor was measured with a Wireless XSens accelerometer and hand tremor by the Optitrack V120 Trio (MOCAP) and the tremor amplitude was computed. We included 24 patients fulfilling the criteria for ET (12 M, 12 F, mean age 58, SD 10) and 26 patients with cervical dystonia (5 M, 21 F mean age 64, SD 10). In supine position, visible head tremor disappeared in 5 out of 13 ET (38%) and in 8 out of 20 DT patients (40%). In ET patients, we found a strong correlation between the amplitudes of head tremor in sitting and supine position (rho=0.91, p Measurement of hand tremor with MOCAP confirmed the predicted difference in tremor of the upper limbs in patients with ET and DT. In the contrary, the analysis of head tremor amplitude did not confirm the hypothesis that head tremor disappears in supine position in patients with ET. The correlations show that the ET is just suppressed and depends on its amplitude. DT suppression is unpredictable.

Turning is an essential movement and has been shown to be a relevant measure for differentiating pathologies. Nowadays, turn analyses utilizing inertial measurement units (IMU) have expanded. Although several IMU-based turn metrics exist, there is no information on the repeatability of turn signals and on the existence of signal patterns shared across subjects. Also, the variability of IMU signals within various subject groups has not been estimated yet. This paper presents an analysis of turn angular velocity and acceleration provided by IMU and tests them for repeatability, patterns, and variability within groups of healthy and diseased subjects. Intra-class correlation and methods for estimating prediction bands, namely the Gaussian point-by-point and bootstrap method, were employed to analyze turn signals from Parkinson disease patients and a control group. The yaw angular velocity demonstrated the highest repeatability in both groups as well as reliability of a shared pattern (p = 0.79 and 0.86). The bootstrap method showed wider bands and higher true coverage in comparison to its Gaussian counterpart. From the results of the performed analysis, we recommend the bootstrap method for determining prediction bands. We also recommend the yaw angular velocity as the signal to be assessed in turn analysis.

Gait symmetry has been shown to be a relevant measure for differentiating between normal and pathological gait. Although a number of symmetry methods exist, it is not clear which of these methods should be used as they have been developed using data collected from varying experimental protocols. This paper presents a comparison of state-of-the-art waveform-based symmetry methods and tests them on walking data collected from different environments. Acceleration signals collected from the ankle are used to analyse symmetry methods under different signal circumstances, such as phase shift, waveform shape difference, signal length (i.e. number of gait cycles) and gait initiation phase. The cyclogram based method is invariant to signal phase shifts, signal length and the gait initiation phase. The trend symmetry method is not affected by signal scaling and the gait initiation phase but is affected by signal length depending on the environment. Similar to the trend method, the cross-correlation symmetry method is not responsive to signal scaling and the gait initiation phase. The results of the symbolic method are not influenced by signal scaling, gait initiation and depending on the environment by the signal phase shift. From the results of the performed analysis, we recommend the trend method to gait symmetry assessment. The comparison of waveform-based symmetry methods brings new knowledge that will help in selecting an appropriate method for gait symmetry assessment under different experimental protocols.

Deep brain stimulation (DBS) of the human basal ganglia is an important therapeutical method of alleviating the symptoms of dystonias of various aetiology. Accurate targeting of the permanent stimulation electrode into the Globus Pallidus internus (GPi) is key to positive long-term effects. The suitability of the location is preoperatively assessed by microelectrodes that register single-unit neuronal activity. The aim of this paper is to analyse electrophysiological recordings of patient's neuronal activity with a focus on the identification of markers relevant to the patient's clinical state. Specific biomarkers may help determine targets and patient-specific protocols for neuromodulation therapy. In this study, 13 patients chronically treated with double-sided DBS GPi were examined with microrecordings. The signal (24 kHz) processing included bandpass filtering (0.5–5 kHz), automated detection of the artefacts, and feature extraction. The results show that the GPi was distinguished from its vicinity with p

Microelectrode arrays (MEA) are extensively used for recording and stimulating neural activity in vitro and in vivo. Depositing nanostructured boron doped diamond (BDD) onto the neuroelectrodes makes it possible to obtain dual mode low-noise neuroelectrical and neurochemical information simultaneously. The signal processing procedure requires finding and distinguishing individual neurons spikes in the recordings. Spike identification is usually done manually which is inaccurate and inappropriate for complex datasets. In this paper, we present a methodology and two algorithms for neurons recognition and evaluation based on unsupervised learning. Forty-five extracellular randomly selected signals from 26 unique measurements of embryonic hippocampal rat neurons (20 kHz, 6 min) were recorded on the commercial 60 TiN channels MEA. The signals were filtered in the 300–3000 Hz band and an amplitude detector (4x std of the background noise) was used for spike detection. WaveClus features were computed and its 3 PCA components were extracted for every spike. The optimal number of clusters were evaluated by an expert rater. K-means + gap criterion (alg. 1) and the Gaussian Mixture Model + Bayesian Information Criterion (alg. 2) were implemented and compared. The total IntraClass Correlation showed a significant inter-rater agreement for all 3 rater procedures (ICC = 0.69, p < 0.001), when post hoc weighted Cohen’s Kappas for 2 raters were 0.85 (expert vs. alg. 1; p < 0.001) and 0.62 (expert vs. alg. 2; p < 0.001). This will contribute to the objective definition of dual mode BDD MEA performance criteria and for a comparison with the current system.

The Timed Up and Go test (TUG) is widely used in both research and clinical settings. The most common parameter for quantification of functional decline is the duration of a performed TUG. Analysis of the turn part of the TUG could provide valuable information about functional decline. Notwithstanding, there are only a few studies that deals with the TUG turn processing. This study proposes a novelty parameter—wave kurtosis (WK) that provides quantitative metrics for describing and comparing turn patterns. The WK is designed to evaluate the shape of the signal waveform. The WK quantifies the peak of the signal, its position and tails. The TUG-turn angular rate was analysed. Intra-class correlations (ICC) of WK and the strength of a linear association between WK and established turn parameters (turn duration, peak angular rate, and mean angular rate) were calculated. The reliability of WK about the vertical axis was moderate (ICC > 0.50), while reliabilities of the frontal axis and sagittal axis varied according to the subject group. The WK about the vertical axis was moderately correlated with turn duration, mean value and peak value. Utilization of waveform parameters opens a new area of TUG turn analysis and may allow for a more sensitive determination of movement disorders or fall risk assessment. Therefore, future studies utilizing turn movement may benefit from the use of the wave kurtosis.

Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI.

The aim is to presents a solution and realization of the design of new split-belt treadmill for controlled, unexpected perturbation during walking to study recovery responses and dynamic stability of the human gait. The construction of the split-belt treadmill consists of several subsystems. The most important subsystems are: actuator, control and sensory subsystem. Actuator subsystem is based on two asynchronous motors, two inverters and two gears (for each belt separately). Control subsystem is made up of Modbus communications between the control computer and two inverters with respect to the parameters of the asynchronous motors. The sensory subsystem is based on the incremental angular speed sensor used to record the behavior of the treadmill belts. The control itself is created through the MatLab software and special custom-made user interface that allows to define a wide range of perturbation schemes. It was then verified whether the belts had the desired speed. Verification of the system has shown that at the recommended speeds of running the belts (at 2.4 km/h), the system is stable, shows no variations in proband load, and real changes in belt velocities are achieved with minimum deviations from the desired values. The main benefit of the described work is the creation of a functional control of the prototype of the treadmill for controlled, mechanical gait perturbations. The split-belt treadmill is designed to study reactive responses during walking that can be further used to fall-risk assessment, clinical or rehabilitation intervention.

We developed a software program, BradykAn, that computes motion characteristics and processes data acquired from compact optical motion capture systems (MoCap) such as Optitrack V120: Trio which provides accurate and easily acquired information about 3-dimensial movement. BradykAn has implemented algorithms and protocols for the evaluation of Unified Parkinson's Disease Rating Scale hand motor tests. The BradykAn was validated on a finger tapping test for patients with Parkinson Disease (PD), where the parameters describing repetitive movement speed, amplitude, and frequency were computed. We examined 55 PD patients (29M,26F), mean age 65 (46–85) years, H&Y stage 2 (1–2.5) and 59 (28M,31F) normal controls, mean age 65 (41–83) years. The analysis delivered significant results in most parameters. The best amplitude decrement parameter (p

The article focuses on a method of quantifying movement of patients with Parkinson's disease (PD) using wearable motion capture (MoCap) system and bilateral cyclograms. The method uses cyclogram characteristics such as the slope, second moment of area and the area of the cyclogram to compare movements of left and right side of body. For symmetric movement, cyclogram should lie on a symmetry line passing through the origin inclined at an angle 45°. To study the body movement, measurement was performed using accelerometers (Xsens Technologies B.V.). Four accelerometers were placed on subject's arms and legs to measure accelerations in the anterior-posterior, medial-lateral and inferior-superior directions. Subjects (patients and healthy subjects) accomplished an extended Timed Up & Go Test (TUG). The data from the accelerometers were preprocessed, and then the bilateral cyclograms of two synchronized accelerations were created and evaluated. Using the cyclograms we confirmed the hypothesis that patients with PD have asymmetrical movements of the limbs. Omitting medication 24 hours before the measurement in patients with early stage PD had little effect on the synkinesias of gait. Findings suggest the possibility of the designed application of wearable MoCap system and bilateral cyclograms for use in drug therapy by evaluating postural stability via measuring accelerations. Thus, method using accelerometers and bilateral cyclograms is newly proposed for patients with PD.

More than half of Parkinson’s disease patients (PD) report difficulty in turning. We observed different numbers of turn steps, turn times, turn types, and turn qualities in PD patients compared to healthy adults. Although medication has an effect on motor impairments in PD, its effect on the complex walking turn task is still unclear. The aim of this paper is to investigate the effect of medication on the walking turn. All subjects performed an instrumented extended Timed Up & Go Test (TUG) wearing gyro-accelerometers. The PD patients were assessed twice, first after a withdrawal of medication (OFF) and then after taking a dose of medication (ON). The parameters calculated were duration, mean and the wave kurtosis of the angular rate. The mean angular rate and the waveform kurtosis showed significant differences between the CG and ON (p Our findings showed a difference in some turning parameters, namely duration and mean angular rate, between PD patients with and without medication. According to our results, medication decreases turn duration. Moreover, the mean angular rate increased with medication. These results support the view that turning is positively affected by medication.

Intraoperative microelectrode records (MER) are considered as the standard electrophysiological method for the precise positioning of the deep brain stimulation (DBS) electrode into the Globus pallidus interna (GPi). The final GPi position is chosen based on the firing patterns of individual neurons. Finding the number of neurons is usually done manually during the spike sorting. We propose methodology for neurons recognition based on the unsupervised learning. Thirty MERs (24 kHz 10s) of the basal ganglia from 10 patients (43.3(±14), 5F) with dystonia were recorded during DBS implantation. MERs were filtered in the 300–3000 Hz band and the amplitude detector (3× std of the background noise) was used to detect spikes. The WaveClus features were computed and its 2 PCA components were extracted for every spike. The optimal number of clusters evaluated by an expert rater, K-means + gap criterion (alg. 1) and the GMM + BIC (alg. 2) were analyzed. The total Intraclass correlation showed a significant inter-rater agreement for all 3 rater procedures (ICC = 0.62, p It can contribute to better description of type of the GPi neurons involved in (non)motor functions. Supported by the GACR No. 16-13323S and AZV No. 16-28119a.

It is currently unknown whether speech and limb motor effectors in Parkinson’s disease (PD) are controlled by similar underlying brain processes. Based on computerized objective analysis, the aim of this study was to evaluate potential correlation between speech and mechanical tests of upper limb motor function. Speech and upper limb motor tests were performed in 22 PD patients and 22 healthy controls. Quantitative acoustic analyses of eight key speech dimensions of hypokinetic dysarthria, including quality of voice, sequential motion rates, consonant articulation, vowel articulation, average loudness, loudness variability, pitch variability, and number of pauses, were performed. Upper limb movements were assessed using the motor part of the Unified Parkinson’s Disease Rating Scale, contactless three-dimensional motion capture system, blinded expert evaluation, and the Purdue Pegboard Test. Significant relationships were observed between the quality of voice assessed by jitter and amplitude decrement of finger tapping (r = 0.61, p = 0.003), consonant articulation evaluated using voice onset time and expert rating of finger tapping (r = 0.60, p = 0.003), and number of pauses and Purdue Pegboard Test score (r = 0.60, p = 0.004). The current study supports the hypothesis that speech impairment in PD shares, at least partially, similar pathophysiological processes with limb motor dysfunction. Vocal fold vibration irregularities appeared to be influenced by mechanisms similar to amplitude decrement during repetitive limb movements. Consonant articulation deficits were associated with decreased manual dexterity and movement speed, likely reflecting fine motor control involvement in PD.

Introduction Timed performance tests were introduced to overcome the disadvantages of subjective evaluation of bradykinesia in Parkinson’s disease (PD). We aimed to verify their discriminative properties and compare them with the motion capture analysis of finger tapping. Methods We included 22 PD patients (10 M, 12 F), mean age 64 (range 48–82) yrs, Hoehn & Yahr stage 2 (1–2.5) and 22 (10 M, 12 F) normal controls, mean age 66 (41–82) yrs. The key tapping subtest of the Halstead-Reitan battery, the Purdue Pegboard test, and the Bradykinesia-Akinesia Incoordination (BRAIN) test were performed according to the test manuals. The finger tapping subtest of the UPDRS-III, item 23 was recorded using a contactless 3D motion capture system Optitrack-V120. Average frequency (AvgFrq), maximum opening velocity (MaxOpV) and amplitude decrement (AmpDec) were computed and simultaneous video recordings of finger tapping were rated by two experts. Results The AmpDec and MaxOpV motion capture measures best differentiated between PD patients and controls (AUC = 0.87 and 0.81). Of the instrumental tests, only the Purdue Pegboard attained significance in differentiating PD patients from controls (AUC = 0.80). In PD patients, MaxOpV correlated with the finger tapping ratings and BRAIN test, and AvgFrq correlated with the BRAIN and Halstead-Reitan test scores. Moreover, correlations were found between the Purdue Pegboard and finger tapping ratings. Conclusions Contactless 3D motion capture of finger tapping allowed an independent analysis of individual components of bradykinesia, demonstrating the amplitude decrement and maximum opening velocity as the most powerful discriminators between PD patients and controls.

Background Huntington’s disease (HD) is characterised by involuntary chorea like movements, poor balance, slurred speech, difficulty swallowing, personality change and difficulty thinking manifesting in the middle age of the patients. Changes in behaviour, motor skills and learning correlate with progression of the disease. Thus it is necessary to monitor these changes in new animal models. In 2009, we have generated transgenic minipigs (TgHD) expressing N-terminal (548 aa) part of human huntingtin (Htt) containing 126 CAG/CAA repeats. Aims To follow disease development in TgHD minipigs of F0, F1 and F3 generation using motoric and behavioural tests. Methods In order to follow behavioural and motoric changes we introduced stability pull back test, balance bean, seesaw test, up and down step test, and tunnel test. We also initiated to use accelerometers to monitor walking differences. Results We observed higher fear or inability to perform certain tests, delayed learning period mainly in situations inducing stress in our oldest TgHD animals (F0, F1 generations). The significant difference between WT and TgHD minipigs was noticed in the ability to step on and to cross the elevated balance beam. Pull back stability test showed a significant difference in TgHD animals. Wobbly movements of back legs were observed in the five years old animals. The weight of all the oldest animals dropped in 10% in the last year. Conclusions The minipig model starts to show a motoric impairment phenotype, and thus to be a promising model for preclinical testing of new therapeutic approaches of HD. Acknowledgement “The research leading to these results has received funding from the Norwegian Financial Mechanism 2009–2014 and the Ministry of Education, Youth and Sports Project under Contract no. MSMT-28477/2014” (7F14308/2014), and National Sustainability Programme, project number LO1609 (Czech Ministry of Education, Youth and Sports) and RVO: 67985904

Parkinson’s disease is a degenerative disorder of the central nervous system and is exhibited by disturbances of motor function. The progress of Parkinson’s disease is typically documented using the Unified Parkinson’s Disease Rating Scale (UPDRS). One of the sections of the UPDRS includes finger tapping test. The objectification of the movement’s tests needs an accurate measurement tool. We created a contactless 3-dimensional camera capture system with light passive (wireless) reflexive markers for motion measurement. The system consists of two industrial 60 Hz cameras with IR cutoff filters. The system is easy to use, space-saving, transportable, and needs just personal computer for data processing; appropriate solution in an outpatient clinic. The system provides 3-dimensional spherical or hemispherical markers in real-time.

Human gait was observed by camera system to record the position data of main points on human body. The 3D coordinates of the end of foot, ankle, knee, hip, pelvis, shoulder and wrist were stored. The simulation program of human gait was compiled at PC in language C++ using simulation system CDCSIS. The program has an input data - length, mass and inertia moments for each part of human body. The data are transformed according to actual coordinates of points on the body. Then the moving and turning accelerations are calculated and joint forces and moments are determined according to the d’Alembert’s principle. At the conclusion the noise is canceled.

This paper is devoted to the optimization and innovation of the method investigating vestibular system from the technical point of view. The specific method how to evaluate gait function with respect to equilibrium function is cranio-corpo-graphy - CCG. The main aim of this paper is to describe design and development of the system for contactless measurement of immediate body posture based on the evaluation mutual position of join going across shoulders and join of the forehead and occiput CCG. Previous solution was based on utilization of Polaroid and spherical mirror, it means on the analogue technology. System of craniocorpography has been recently computerized. The new system is based on the videotechnology, it means on the TV system with sidelong scanning by TV fisheye camera for increasing of the field of view and the wireless transmission of analogue videosignal. The videosequences are processed by specialized software and data is saved into database. Drawback of the new system is time-consuming videosequence processing only. Advantages of the new system are the following: more evaluated parameters, reduction of trajectory distortion by spherical mirror, exact evaluation of parameters, possibility to evaluate stand test and further parameters, detailed analysis of movement trajectory and imposition of investigation results and off-line analysis. The new system has a lot of advantages and one drawback. Based on the comparison and experiments it seems that the new system is more appropriate than the old one for clinical neurological practice.

In this paper we describe new advanced contactless method for the precise posture head measurement using digital cameras. Objective was to develop a technique for measurement of the native position of the head in 3D space. The technique was supposed to determine differences between anatomical coordinate system and physical coordinate system. Similar technique has not been developed up to this time such that it could be widely and easily used in neurological clinical practice although it could have an important use in this field because there are a lot of neurological disorders that affect postural alignment position of head. The frontal photograph is used to evaluate the coronal head tilt (inclination). A digital camera is situated on a (tripod) special stand so that its position corresponds to the physical horizontal. The anatomical horizontal can be defined by the following ways: If the measured subject does not suffer from an eye disorder that affects position of eyes, the connecting line between eye pupils can then be considered as anatomical horizontal. These points are designated by white rounded marks. The same method is used for evaluating the tilt in sagittal plane (flexion) using a profile photograph. The flexion value is measured relatively as the inclination of the connecting line between tragus and exterior eye corner. The circumvolution extent (rotation) of the head is evaluated from the difference between tragus coordinates in the left-profile and right-profile image. These images are captured at the same time using two cameras and the cameras are situated on the same optical axis which is parallel with the frontal plane of subject. This is achieved by attaching specially designed devices on stand. These devices allow the cameras to be set on the same axis using laser beam. The whole configuration is placed on an axis designated on the floor, or on the special mat. There was experimentally checked that the accuracy of this method in order of tenths of degrees and therefore this method satisfies the general physicians’ requirements for the accuracy of the measurement about 1-2°.