A5014286353- Balance, Gait, and Falls Prevention
- Context-Aware Activity Recognition Systems
- Cerebral Palsy and Movement Disorders
- Parkinson's Disease Mechanisms and Treatments
- Gait Recognition and Analysis
- Non-Invasive Vital Sign Monitoring
- Muscle activation and electromyography studies
- Diabetic Foot Ulcer Assessment and Management
- Neurological disorders and treatments
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Physical Activity and Health
- Stroke Rehabilitation and Recovery
- Injury Epidemiology and Prevention
- Neuroscience and Neural Engineering
- Prosthetics and Rehabilitation Robotics
- Anomaly Detection Techniques and Applications
- Medical Imaging Techniques and Applications
- Hemodynamic Monitoring and Therapy
- Time Series Analysis and Forecasting
- Botulinum Toxin and Related Neurological Disorders
- Morphological variations and asymmetry
- IoT and GPS-based Vehicle Safety Systems
- EEG and Brain-Computer Interfaces
- Hand Gesture Recognition Systems
- Agricultural Engineering and Mechanization
University of Bologna
2016-2025
Laboratori Guglielmo Marconi (Italy)
2016-2025
Marconi University
2016-2025
Scuola Superiore Sant'Anna
2021
Foro Italico University of Rome
2021
Radboud University Nijmegen
2021
Radboud University Medical Center
2021
Newcastle University
2021
Université de Rennes
2021
Oregon Health & Science University
2021
Abstract Background Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper to comparatively assess validate DMOs estimated using gait six different cohorts, focusing on sequence detection, foot initial contact detection (ICD), cadence (CAD) stride length (SL) estimates. Methods Twenty healthy older adults, 20 people Parkinson’s disease,...
Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and bout duration. The goal was provide recommendations on the use of devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Congestive Heart Failure, healthy older adults (n = 97) were monitored in laboratory (2.5 h), using lower back device. Two pipelines validated...
The Timed Up and Go (TUG) test is a clinical to assess mobility in Parkinson's disease (PD). It consists of rising from chair, walking, turning, sitting. Its total duration the traditional outcome. In this study an instrumented TUG (iTUG) was used supplement quantitative information about performance PD subjects: single accelerometer, worn at lower back, record acceleration signals during acceleration-derived measures were extracted recorded signals. aim select reliable identify quantify...
Posture analysis in quiet standing is a key component of the clinical evaluation Parkinson's disease (PD), postural instability being one PD's major symptoms. The aim this study was to assess feasibility using accelerometers characterize behavior early mild PD subjects. Twenty and 20 control subjects, wearing an accelerometer on lower back, were tested five conditions characterized by sensory attentional perturbation. A total 175 measures computed from signals quantify tremor, acceleration,...
Freezing of gait (FOG) is a disabling symptom that common among patients with advanced Parkinson's disease (PD). External cues such as rhythmic auditory stimulation can help PD experiencing freezing to resume walking. Wearable systems for automatic detection have been recently developed. However, these detect FOG episode after it has happened. Instead, in the present study new approach prediction (before actually happens) presented. Prediction might enable preventive cueing, reducing...
Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations quantifying digital outcomes (DMOs) both during supervised structured real-world conditions. The validity IMU-based methods the real-world, however, is still limited populations. Rigorous validation...
Introduction: Accurately assessing people’s gait, especially in real-world conditions and case of impaired mobility, is still a challenge due to intrinsic extrinsic factors resulting gait complexity. To improve the estimation gait-related digital mobility outcomes (DMOs) scenarios, this study presents wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units two distance sensors). Methods: The INDIP technical...
Abstract Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual’s mobility. Still, heterogeneity protocols, sensor characteristics, data formats, gold standards represent a barrier for sharing, reproducibility, external validation. In this study, we aim at providing example of how (from the real-world laboratory) recorded from different wearables standard technologies can be organized, integrated, stored....
Background Wrist-worn inertial sensors are used in digital health for evaluating mobility real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, detection is an important step to identify regions interest where occurs, which requires robust algorithms due complexity arm movements. While exist other sensor positions, a comparative validation applied wrist position on data sets across different disease populations missing. Furthermore,...
Abstract Background Cueing can alleviate freezing of gait (FOG) in people with Parkinson's disease (PD), but using the same cues continuously daily life may compromise effectiveness. Therefore, we developed DeFOG‐system to deliver personalized auditory on detection a FOG episode. Objectives We aimed evaluate effects DeFOG during FOG‐provoking protocol: (1) after 4 weeks DeFOG‐use against an active control group; (2) immediate (within‐group) different medication states. Method In this...
Falls are a common, serious threat to the health and self-confidence of elderly. Assessment fall risk is an important aspect effective prevention programs.In order test whether it possible outperform current prognostic tools for falls, we analyzed 1010 variables pertaining mobility collected from 976 elderly subjects (InCHIANTI study). We trained validated data-driven model that issues probabilistic predictions about future falls. benchmarked against other indicators: history gait speed,...
Real-world fall events objectively measured by body-worn sensors can improve the understanding of in older people. However, these are rare and hence challenging to capture. Therefore, FARSEEING (FAll Repository for design Smart sElf-adaptive Environments prolonging Independent livinG) consortium associated partners started build up a meta-database real-world falls.Between January 2012 December 2015 more than 300 have been recorded. This is currently largest collection data recorded with...
Physical activity is strongly linked with mental and physical health in the elderly population accurate monitoring of activities daily living (ADLs) can help improve quality life well-being. This study presents validates an inertial sensors-based classification system developed older adults as target population. The dataset was collected free-living conditions without placing constraints on way order performing ADLs. Four sensor locations (chest, lower back, wrist, thigh) were explored to...
Falling is a significant health problem. Fall detection, to alert for medical attention, has been gaining increasing attention. Still, most of the existing studies use falls simulated in laboratory environment test obtained performance. We analyzed acceleration signals recorded by an inertial sensor on lower back during 143 real-world (the extensive collection date) from FARSEEING repository. Such data were continuous monitoring subjects with moderate-to-high risk falling. designed and...
About 30% of people over 65 are subject to at least one unintentional fall a year. Fall prevention protocols and interventions can decrease the number falls. To be effective, strategy requires prior step evaluate risk subjects. Despite extensive research, existing assessment tools for have been insufficient predicting falls.The goal this study is present novel web-based fall-risk tool (FRAT-up) its accuracy in falls, within context community-dwelling persons aged up.FRAT-up based on...
Walking/gait speed is a key measure for daily mobility characterization. To date, various studies have attempted to design algorithms estimate walking using an inertial sensor worn on the lower back, which considered as proper location activity monitoring in life. However, these were rarely compared and validated same datasets, including people with different preferred speed. This study implemented several original, improved, new estimating cadence, step length eventually We designed...
Tremor is one of the symptoms several disorders central and peripheral nervous system, such as Parkinson's disease (PD). The impairment postural control another symptom PD. conventional method posture analysis uses force plates, but accelerometers can be a valid reliable alternative. Both these measurement techniques are sensitive to tremor. affects measures may thus lead misleading results or interpretations. Linear low-pass filters (LPFs) commonly employed for tremor removal. In this...
Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim this work is present novel wavelet-based approach detection, focusing on impact phase and using dataset real-world falls. Since recorded result in non-stationary signal, wavelet transform was chosen examine patterns. idea consider average pattern as “prototype...
Introduction The clinical validity of real-world walking cadence in people with COPD is unsettled. Our objective was to assess the levels, variability and association clinically relevant characteristics outcomes cadence. Methods We assessed (steps per minute during bouts longer than 10 s) from 7 days’ accelerometer data 593 individuals five European countries, functional validated questionnaires standardised tests. Severe exacerbations a 12-month follow-up were recorded patient reports...
In this study, the use of an instrumented balance test based on inertial sensors was evaluated in patients with Parkinson's disease (PD). We aimed to objectively characterize motor subtypes PD [tremor dominant (TD) and postural instability gait difficulty (PIGD)], help quantitatively classify subjects into subtypes. Subjects were studied performing tests, while wearing a device including tri-axial accelerometer lower back, four different experimental conditions that depended feet position...
The popularity of using wearable inertial sensors for physical activity classification has dramatically increased in the last decade due to their versatility, low form factor, and power requirements. Consequently, various systems have been developed automatically classify daily life activities. However, scope implementation such is limited laboratory-based investigations. Furthermore, these are not directly comparable, large diversity design (e.g., number sensors, placement data collection...
The L-test is a performance-based measure to assess balance and mobility. Currently, the primary outcome from this test time required finish it. In study we present instrumented (iL-test), an wherein mobility evaluated by means of wearable inertial sensor worn at lower back. We analyzed data 113 people across seven cohorts: healthy adults, chronic obstructive pulmonary disease, multiple sclerosis, congestive heart failure, Parkinson's proximal femoral fracture, transfemoral amputation....