OBJECTIVE: To date, very few studies have focused on structural changes and their association with cognitive performance in isolated REM sleep behaviour disorder (iRBD). Moreover, the results of these studies are inconclusive. This study aims to evaluate differences in the associations between brain morphology and cognitive tests in iRBD and healthy controls. METHODS: Sixty-three patients with iRBD and thirty-six controls underwent MRI with a 3 T scanner. The cognitive performance was assessed by a comprehensive neuropsychological battery. Based on performance, the iRBD group was divided into two subgroups with (iRBD-MCI) and without mild cognitive impairment (iRBD-NC). The high-resolution T1-weighted images were analysed using an automated atlas segmentation tool, voxel-based (VBM) and deformation-based (DBM) morphometry to identify between-group differences and correlations with cognitive performance. RESULTS: VBM, DBM and the comparison of ROI volumes yielded no significant differences between iRBD and controls. In the iRBD group, significant correlations in VBM were found between several cortical and subcortical structures primarily located in the temporal, parietal, occipital lobe, cerebellum, and basal ganglia and three cognitive tests assessing psychomotor speed and one memory test. Between-group analysis of cognition revealed a significant difference between iRBD-MCI and iRBD-NC in tests including a processing speed component. CONCLUSIONS: iRBD shows deficits in several cognitive tests that correlate with morphological changes, the most prominent of which is in psychomotor speed and visual attention as measured by the TMT-A and associated with the volume of striatum, insula, cerebellum, temporal lobe, pallidum and amygdala.
In Parkinson's disease (PD), impaired gait and cognition affect daily activities, particularly in the more advanced stages of the disease. This study investigated the relationship between gait parameters, cognitive performance, and brain morphology in patients with early untreated PD. 64 drug-naive PD patients and 47 healthy controls (HC) participated in the study. Single- and dual-task gait (counting task) were examined using an expanded Timed Up & Go Test measured on a GaitRite walkway. Measurements included gait speed, stride length, and cadence. A brain morphometry analysis was performed on T1-weighted magnetic resonance (MR) images. In PD patients compared to HC, gait analysis revealed reduced speed (p < 0.001) and stride length (p < 0.001) in single-task gait, as well as greater dual-task cost (DTC) for speed (p = 0.007), stride length (p = 0.014) and cadence (p = 0.029). Based on the DTC measures in HC, PD patients were further divided into two subgroups with normal DTC (PD-nDTC) and abnormally increased DTC (PD-iDTC). For PD-nDTC, voxel-based morphometric correlation analysis revealed a positive correlation between a cluster in the left primary motor cortex and stride-length DTC (r = 0.57, p = 0.027). For PD-iDTC, a negative correlation was found between a cluster in the right lingual gyrus and the DTC for gait cadence (r=-0.35, pFWE = 0.018). No significant correlations were found in HC. The associations found between brain morphometry and gait performance with a concurrent cognitive task may represent the substrate for gait and cognitive impairment occurring since the early stages of PD.
- MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- mozek * diagnostické zobrazování patologie patofyziologie MeSH
- neurologické poruchy chůze * etiologie patofyziologie diagnostické zobrazování patologie MeSH
- neuropsychologické testy MeSH
- Parkinsonova nemoc * diagnostické zobrazování patofyziologie patologie komplikace MeSH
- senioři MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Due to the ever-increasing proportion of older people in the total population and the growing awareness of the importance of protecting workers against physical overload during long-time hard work, the idea of supporting exoskeletons progressed from high-tech fiction to almost commercialized products within the last six decades. Sensors, as part of the perception layer, play a crucial role in enhancing the functionality of exoskeletons by providing as accurate real-time data as possible to generate reliable input data for the control layer. The result of the processed sensor data is the information about current limb position, movement intension, and needed support. With the help of this review article, we want to clarify which criteria for sensors used in exoskeletons are important and how standard sensor types, such as kinematic and kinetic sensors, are used in lower limb exoskeletons. We also want to outline the possibilities and limitations of special medical signal sensors detecting, e.g., brain or muscle signals to improve data perception at the human-machine interface. A topic-based literature and product research was done to gain the best possible overview of the newest developments, research results, and products in the field. The paper provides an extensive overview of sensor criteria that need to be considered for the use of sensors in exoskeletons, as well as a collection of sensors and their placement used in current exoskeleton products. Additionally, the article points out several types of sensors detecting physiological or environmental signals that might be beneficial for future exoskeleton developments.
- MeSH
- biomechanika MeSH
- dolní končetina fyziologie MeSH
- exoskeleton * MeSH
- lidé MeSH
- pohyb fyziologie MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
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.
- MeSH
- deep learning * MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- melaniny analýza MeSH
- počítačové zpracování obrazu MeSH
- prodromální symptomy MeSH
- senioři MeSH
- studie případů a kontrol MeSH
- substantia nigra diagnostické zobrazování MeSH
- synukleinopatie diagnostické zobrazování MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- klinické zkoušky MeSH
