Towards a wearable system for predicting the freezing of gait in people affected by Parkinson's disease

Some wearable solutions exploiting on-body acceleration sensors have been proposed to recognize Freezing of Gait (FoG) in people affected by Parkinson Disease (PD). Once a FoG event is detected, these systems generate a sequence of rhythmic stimuli to allow the patient restarting the march. While these solutions are effective in detecting FoG events, they are unable to predict FoG to prevent its occurrence. This paper fills in the gap by presenting a machine learning-based approach that classifies accelerometer data from PD patients, recognizing a pre-FOG phase to further anticipate FoG occurrence in advance. Gait was monitored by three tri-axial accelerometer sensors worn on the back, hip and ankle. Gait features were then extracted from the accelerometer's raw data through data windowing and non-linear dimensionality reduction. A k-nearest neighbor algorithm (k-NN) was used to classify gait in three classes of events: pre-FoG, no-FoG and FoG. The accuracy of the proposed solution was compared to state of-the-art approaches. Our study showed that: (i) we achieved performances overcoming the state-of-the-art approaches in terms of FoG detection, (ii) we were able, for the very first time in the literature, to predict FoG by identifying the pre-FoG events with an average sensitivity and specificity of, respectively, 94.1% and 97.1%, and (iii) our algorithm can be executed on resource-constrained devices. Future applications include the implementation on a mobile device, and the administration of rhythmic stimuli by a wearable device to help the patient overcome the FoG

Twelve-year follow-up of a large italian family with atypical phenotypes of DYT1-dystonia

Background: A heterozygous mutation in the TOR1A gene (DYT1) accounts for isolated dystonia typically presenting during childhood or adolescence, with initial involvement of one limb, spreading rapidly to other limbs and the trunk, sparing craniocervical muscles. However, atypical phenotypes, regarding age at onset, site of presentation, and spreading have been reported. Methods and Findings: In 2006, we described a large Italian family showing atypical phenotypes and intrafamilial clinical variability of DYT1-dystonia. The current article reports on a 12-year follow-up of this family, focusing on disease onset in three previously asymptomatic DYT1 mutation carriers, and the reassessment of initially affected individuals. Conclusions: The new cases confirm the intrafamilial phenotypic heterogeneity of DYT1-dystonia. Moreover, this case series highlights that symptoms in atypical phenotypes seem not to spread significantly and in the long term, rarely worsen. Prolonged follow-up of DYT1-positive pedigrees may expand the clinical spectrum of DYT1-dystonia. \ua9 2018 International Parkinson and Movement Disorder Societ

Brain 18F-FDG and 18F-Flumetamol PET Imaging of Fragile X-Associated Tremor Ataxia Syndrome

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a rare movement disorder caused by a 55-to-200 CGG-trinucleotide expansion premutation in the FMR1 gene. Core diagnostic criteria are tremor, ataxia, and T2-weighted hyperintensity of the middle cerebellar peduncles on MRI, but FXTAS encompass a broad spectrum of neurological symptoms. FXTAS pathophysiology is largely unknown, and some animal models and neuropathology findings suggest possible overlap with Alzheimer disease. We report the combined PET imaging of a genetically confirmed FXTAS patient, presenting reduced temporal-frontal 18F-FDG uptake, and pathological cortical deposition of amyloid to 18F-flumetamol PET scan. This report may offer clues to FXTAS pathophysiology

Levofloxacin-induced hemichorea-hemiballism in a patient with previous thalamic infarction

[no abstract available

Cerebral large-vessel vasculitis as an unusual manifestation of POEMS syndrome

non present

Abnormal nociceptive processing occurs centrally and not peripherally in pain-free Parkinson disease patients: A study with laser-evoked potentials

Background Several studies documented abnormal nociceptive processing in PD patients. Pain central pathways are accessible by laser-evoked potentials (LEPs). LEPs recording show a N2/P2 complex mostly generated by the anterior cingulate cortex, preceded by an earlier negative component (N1), originating from the opercular cortex. Previous work demonstrated N2/P2 amplitude reduction in PD patients and suggested a centrally-acting pathomechanism for the genesis of pain. However, since a peripheral deafferentation has been recently demonstrated in PD, it is not clear if such LEP abnormalities reflect a mechanism acting centrally or not. Objective To assess whether abnormalities of nociceptive inputs occur at central and/or peripheral level in pain-free PD patients with hemiparkinson using Nd:YAP LEPs. Methods We recorded scalp Nd:YAP-LEPs to hand stimulation in 13 pain-free patients with unilateral PD and in 13 healthy subjects. Additionally, we collected laser pain-rating in both groups. Results PD patients and normal subjects showed comparable N1, N2 and P2 latencies. The N2/P2 amplitude was significantly lower in PD patients than in controls, regardless of the clinically affected side, whereas the N1/P1 amplitude was not different. PD patients had higher pain-rating, indicative of hyperalgesia. Conclusions These findings demonstrate that in the PD patients the abnormal processing of pain stimuli occurs at central rather than peripheral level. The co-existence of hyperalgesia and reduced amplitude of the N2/P2 complex, in spite of a normal N1/P1 component, suggests an imbalance between the medial and lateral pain systems. Such a dissociation might explain the genesis of central pain in PD

Levofloxacin-induced hemichorea-hemiballism in a patient with previous thalamic infarction

[no abstract available

A low-cost wireless body area network for human activity recognition in healthy life and medical applications

Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more emerging as a central system for the implementation of solutions for well-being and healthcare. In fact, by elaborating the data collected by a WBAN, advanced classification models can accurately extract health-related parameters, thus allowing, as examples, the implementations of applications for fitness tracking, monitoring of vital signs, diagnosis, and analysis of the evolution of diseases, and, in general, monitoring of human activities and behaviours. Unfortunately, commercially available WBANs present some technological and economic drawbacks from the point of view, respectively, of data fusion and labelling, and cost of the adopted devices. To overcome existing issues, in this paper, we present the architecture of a low-cost WBAN, which is built upon accessible off-the-shelf wearable devices and an Android application. Then, we report its technical evaluation concerning resource consumption. Finally, we demonstrate its versatility and accuracy in both medical and well-being application scenarios

Medial temporal lobe atrophy and posterior atrophy scales normative values

The medial temporal lobe atrophy (MTA) and the posterior atrophy (PA) scales allow to assess the degree hippocampal and parietal atrophy from magnetic resonance imaging (MRI) scans. Despite reliable, easy and widespread employment, appropriate normative values are still missing. We aim to provide norms for the Italian population