Hyposmia correlates with axial signs and gait disorder in Parkinson's disease: an Italian Olfactory Identification Test study.

Background: Olfactory dysfunction is a non-motor symptom and an important biomarker of Parkinson's disease (PD) because of its high prevalence (> 90%). Whether hyposmia correlates with motor symptoms is unclear. In the present study, we aim to investigate the relationship between olfactory impairment with both motor and non-motor features and disease variables (disease duration, stage, and severity).

A Comprehensive Review of COVID-19-Related Olfactory Deficiency: Unraveling Associations with Neurocognitive Disorders and Magnetic Resonance Imaging Findings.

Olfactory dysfunction (OD) is one of the most common symptoms in COVID-19 patients and can impact patients' lives significantly. The aim of this review was to investigate the multifaceted impact of COVID-19 on the olfactory system and to provide an overview of magnetic resonance (MRI) findings and neurocognitive disorders in patients with COVID-19-related OD. Extensive searches were conducted across PubMed, Scopus, and Google Scholar until 5 December 2023.

Hands-feet wireless devices: Test-retest reliability and discriminant validity of motor measures in Parkinson's disease telemonitoring.

Background: Telemonitoring, a branch of telemedicine, involves the use of technological tools to remotely detect clinical data and evaluate patients. Telemonitoring of patients with Parkinson's disease (PD) should be performed using reliable and discriminant motor measures. Furthermore, the method of data collection and transmission, and the type of subjects suitable for telemonitoring must be well defined.

Testing olfactory dysfunction in acute and recovered COVID-19 patients: a single center study in Italy.

Background: Olfactory dysfunction in coronavirus disease 2019 (COVID-19) is common during acute illness and appears to last longer than other symptoms. The aim of this study was to objectively investigate olfactory dysfunction in two cohorts of patients at two different stages: during acute illness and after a median recovery of 4 months.

Methods: Twenty-five acutely ill patients and 26 recovered subjects were investigated.

Biomechanical parameters assessment for the classification of Parkinson Disease using Bidirectional Long Short-Term Memory.

Nowadays objective and efficient assessment of Parkinson Disease (PD) with machine learning techniques is a major focus for clinical management. This work presents a novel approach for classification of patients with PD (PwPD) and healthy controls (HC) using Bidirectional Long Short-Term Neural Network (BLSTM). In this paper, the SensHand and the SensFoot inertial wearable sensors for upper and lower limbs motion analysis were used to acquire motion data in thirteen tasks derived from the MDS-UPDRS III.