Monipar: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms.

Objective: This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation.

Preclinical examination of early-onset thalamic-cortical seizures after hemispheric stroke.

Objective: Ischemic stroke is one of the main causes of death and disability worldwide and currently has limited treatment options. Electroencephalography (EEG) signals are significantly affected in stroke patients during the acute stage. In this study, we preclinically characterized the brain electrical rhythms and seizure activity during the hyperacute and late acute phases in a hemispheric stroke model with no reperfusion.

Urban Road Surface Discrimination by Tire-Road Noise Analysis and Data Clustering.

The surface condition of roadways has direct consequences on a wide range of processes related to the transportation technology, quality of road facilities, road safety, and traffic noise emissions. Methods developed for detection of road surface condition are crucial for maintenance and rehabilitation plans, also relevant for driving environment detection for autonomous transportation systems and e-mobility solutions. In this paper, the clustering of the tire-road noise emission features is proposed to detect the condition of the wheel tracks regions during naturalistic driving events.

How the COVID-19 Pandemic Muted and Remixed the World's Acoustics for a While.

Purpose Of Review: This review aims to analyze the effects of the pandemic on the world's sound environment.

Recent Findings: The confinements associated with the pandemic led to a reduction in sound levels worldwide and a change in the perception of soundscapes in the absence of traffic noise and human-generated noise.

Summary: In response to the COVID-19 pandemic, many countries and regions around the world adopted a series of interventions in 2020 that have been referred to as "lockdown" or "confinement.

Improved Estimation of End-Milling Parameters from Acoustic Emission Signals Using a Microphone Array Assisted by AI Modelling.

This paper presents the implementation of a measurement system that uses a four microphone array and a data-driven algorithm to estimate depth of cut during end milling operations. The audible range acoustic emission signals captured with the microphones are combined using a spectral subtraction and a blind source separation algorithm to reduce the impact of noise and reverberation. Afterwards, a set of features are extracted from these signals which are finally fed into a nonlinear regression algorithm assisted by machine learning techniques for the contactless monitoring of the milling process.

Sleep-Wake Cycle and EEG-Based Biomarkers during Late Neonate to Adult Transition.

During the transition from neonate to adulthood, brain maturation establishes coherence between behavioral states-wakefulness, non-rapid eye movement, and rapid eye movement sleep. In animal models few studies have characterized and analyzed cerebral rhythms and the sleep-wake cycle in early ages, in relation to adulthood. Since the analysis of sleep in early ages can be used as a predictive model of brain development and the subsequent emergence of neural disturbances in adults, we performed a study on late neonatal mice, an age not previously characterized.

Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.

Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives.

Changes in noise levels in the city of Madrid during COVID-19 lockdown in 2020.

The lockdown that Madrid has suffered during the months of March to June 2020 to try to control and minimize the spread of COVID-19 has significantly altered the acoustic environment of the city. The absence of vehicles and people on the streets has led to a noise reduction captured by the monitoring network of the City of Madrid. In this article, an analysis has been carried out to describe the reduction in noise pollution that has occurred and to analyze the changes in the temporal patterns of noise, which are strongly correlated with the adaptation of the population's activity and behavior to the new circumstances.

A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown.

Many countries around the world have chosen lockdown and restrictions on people's mobility as the main strategies to combat the COVID-19 pandemic. These actions have significantly affected environmental noise and modified urban soundscapes, opening up an unprecedented opportunity for research in the field. In order to enable these investigations to be carried out in a more harmonized and consistent manner, this paper makes a proposal for a set of indicators that will enable to address the challenge from a number of different approaches.

Deep Learning Approaches for Detecting Freezing of Gait in Parkinson's Disease Patients through On-Body Acceleration Sensors.

Freezing of gait (FOG) is one of the most incapacitating motor symptoms in Parkinson's disease (PD). The occurrence of FOG reduces the patients' quality of live and leads to falls. FOG assessment has usually been made through questionnaires, however, this method can be subjective and could not provide an accurate representation of the severity of this symptom.

A Digital Signal Processor Based Acoustic Sensor for Outdoor Noise Monitoring in Smart Cities.

Presently, large cities have significant problems with noise pollution due to human activity. Transportation, economic activities, and leisure activities have an important impact on noise pollution. Acoustic noise monitoring must be done with equipment of high quality.

Beyond sound level monitoring: Exploitation of social media to gather citizens subjective response to noise.

Subjective response to noise is probably the most important goal in environmental acoustics. Traditional surveys have the drawback of high cost deriving from its development and execution, the limited number of participants, and the duration of the surveying campaign. The main drawbacks of online surveys are the low participation, or the self-produced bias that concerns about the topic can raise.

Occupational Risk Prevention through Smartwatches: Precision and Uncertainty Effects of the Built-In Accelerometer.

Wearable technology has had a significant growth in the last years; this is particularly true of smartwatches, due to their potential advantages and ease of use. These smart devices integrate sensors that can be potentially used within industrial settings and for several applications, such as safety, monitoring, and the identification of occupational risks. The accelerometer is one of the main sensors integrated into these devices.

Communicating airport noise emission data to the general public.

Despite the efforts that the aviation industry has undertaken during the last few decades, noise annoyance remains high, partly because of the continuous transport demands of modern societies and partly because of changes in citizen expectations and their growing environmental concerns. Although modern aircraft are considerably quieter than their predecessors, the number of complaints has not decreased as much as expected. Therefore, the aeronautical sector has tried more sociological and/or psychological strategies to gain acceptance through awareness and community engagement.