Elisa Pelosin

Prof. Dr. Elisa Pelosin

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Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2019 in The Lancet Neurology
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Journal Article
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AMAnat Mirelman
Anat Mirelman
PBPaolo Bonato
Paolo Bonato
RCRichard Camicioli
Richard Camicioli
TETerry D Ellis
Terry D Ellis
NGNir Giladi
Nir Giladi
QAQuincy J Almeida
Quincy J Almeida

1 September 2016 in The Lancet
Verified
Journal Article
Open access
AMAnat Mirelman
Anat Mirelman
LRLynn Rochester
Lynn Rochester
IMInbal Maidan
Inbal Maidan
Silvia Del DinSilvia Del Din
Silvia Del Din
Lisa AlcockLisa Alcock
Lisa Alcock
JHJeffrey M Hausdorff
Jeffrey M Hausdorff
Age-associated motor and cognitive deficits increase the risk of falls, a major cause of morbidity and mortality. Because of the significant ramifications of falls, many interventions have been proposed, but few have aimed to prevent falls via an integrated approach targeting both motor and cognitive function. We aimed to test the hypothesis that an intervention combining treadmill training with non-immersive virtual reality (VR) to target both cognitive aspects of safe ambulation and mobility would lead to fewer falls than would treadmill training alone. We carried out this randomised controlled trial at five clinical centres across five countries (Belgium, Israel, Italy, the Netherlands, and the UK). Adults aged 60-90 years with a high risk of falls based on a history of two or more falls in the 6 months before the study and with varied motor and cognitive deficits were randomly assigned by use of computer-based allocation to receive 6 weeks of either treadmill training plus VR or treadmill training alone. Randomisation was stratified by subgroups of patients (those with a history of idiopathic falls, those with mild cognitive impairment, and those with Parkinson's disease) and sex, with stratification per clinical site. Group allocation was done by a third party not involved in onsite study procedures. Both groups aimed to train three times per week for 6 weeks, with each session lasting about 45 min and structured training progression individualised to the participant's level of performance. The VR system consisted of a motion-capture camera and a computer-generated simulation projected on to a large screen, which was specifically designed to reduce fall risk in older adults by including real-life challenges such as obstacles, multiple pathways, and distracters that required continual adjustment of steps. The primary outcome was the incident rate of falls during the 6 months after the end of training, which was assessed in a modified intention-to-treat population. Safety was assessed in all patients who were assigned a treatment. This study is registered with ClinicalTrials.gov, NCT01732653. Between Jan 6, 2013, and April 3, 2015, 302 adults were randomly assigned to either the treadmill training plus VR group (n=154) or treadmill training alone group (n=148). Data from 282 (93%) participants were included in the prespecified, modified intention-to-treat analysis. Before training, the incident rate of falls was similar in both groups (10·7 [SD 35·6] falls per 6 months for treadmill training alone vs 11·9 [39·5] falls per 6 months for treadmill training plus VR). In the 6 months after training, the incident rate was significantly lower in the treadmill training plus VR group than it had been before training (6·00 [95% CI 4·36-8·25] falls per 6 months; p<0·0001 vs before training), whereas the incident rate did not decrease significantly in the treadmill training alone group (8·27 [5·55-12·31] falls per 6 months; p=0·49). 6 months after the end of training, the incident rate of falls was also significantly lower in the treadmill training plus VR group than in the treadmill training group (incident rate ratio 0·58, 95% CI 0·36-0·96; p=0·033). No serious training-related adverse events occurred. In a diverse group of older adults at high risk for falls, treadmill training plus VR led to reduced fall rates compared with treadmill training alone. European Commission.

1 January 2016 in Parkinsonism & Related Disorders
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Journal Article
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GAGiovanni Abbruzzese
Giovanni Abbruzzese
RMRoberta Marchese
Roberta Marchese
LALaura Avanzino
Laura Avanzino
EPElisa Pelosin
Elisa Pelosin

30 October 2014 in BioMed Research International
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Journal Article
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CTCarlo Trompetto
Carlo Trompetto
Lucio MarinelliLucio Marinelli
Lucio Marinelli
LMLaura Mori
Laura Mori
EPElisa Pelosin
Elisa Pelosin
ACAntonio Currà
Antonio Currà
GAGiovanni Abbruzzese
Giovanni Abbruzzese
Spasticity is the velocity-dependent increase in muscle tone due to the exaggeration of stretch reflex. It is only one of the several components of the upper motor neuron syndrome (UMNS). The central lesion causing the UMNS disrupts the balance of supraspinal inhibitory and excitatory inputs directed to the spinal cord, leading to a state of disinhibition of the stretch reflex. However, the delay between the acute neurological insult (trauma or stroke) and the appearance of spasticity argues against it simply being a release phenomenon and suggests some sort of plastic changes, occurring in the spinal cord and also in the brain. An important plastic change in the spinal cord could be the progressive reduction of postactivation depression due to limb immobilization. As well as hyperexcitable stretch reflexes, secondary soft tissue changes in the paretic limbs enhance muscle resistance to passive displacements. Therefore, in patients with UMNS, hypertonia can be divided into two components: hypertonia mediated by the stretch reflex, which corresponds to spasticity, and hypertonia due to soft tissue changes, which is often referred as nonreflex hypertonia or intrinsic hypertonia. Compelling evidences state that limb mobilisation in patients with UMNS is essential to prevent and treat both spasticity and intrinsic hypertonia.

3 May 2019 in European Review of Aging and Physical Activity
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Journal Article
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IHInbar Hillel
Inbar Hillel
EGEran Gazit
Eran Gazit
ANAlice Nieuwboer
Alice Nieuwboer
LALaura Avanzino
Laura Avanzino
LRLynn Rochester
Lynn Rochester
Jeffrey HausdorffJeffrey Hausdorff
Jeffrey Hausdorff
The traditional evaluation of gait in the laboratory during structured testing has provided important insights, but is limited by its “snapshot” character and observation in an unnatural environment. Wearables enable monitoring of gait in real-world environments over a week. Initial findings show that in-lab and real-world measures differ. As a step towards better understanding these gaps, we directly compared in-lab usual-walking (UW) and dual-task walking (DTW) to daily-living measures of gait. In-lab gait features (e.g., gait speed, step regularity, and stride regularity) derived from UW and DTW were compared to the same gait features during daily-living in 150 elderly fallers (age: 76.5 ± 6.3 years, 37.6% men). In both settings, features were extracted from a lower-back accelerometer. In the real-world setting, subjects were asked to wear the device for 1 week and pre-processing detected 30-s daily-living walking bouts. A histogram of all walking bouts was determined for each walking feature for each subject and then each subject’s typical (percentile 50, median), worst (percentile 10) and the best (percentile 90) values over the week were determined for each feature. Statistics of reliability were assessed using Intra-Class correlations and Bland-Altman plots. As expected, in-lab gait speed, step regularity, and stride regularity were worse during DTW, compared to UW. In-lab gait speed, step regularity, and stride regularity during UW were significantly higher (i.e., better) than the typical daily-living values (p < 0.001) and different (p < 0.001) from the worst and best values. DTW values tended to be similar to typical daily-living values (p = 0.205, p = 0.053, p = 0.013 respectively). ICC assessment and Bland-Altman plots indicated that in-lab values do not reliably reflect the daily-walking values. Gait values measured during relatively long (30-s) daily-living walking bouts are more similar to the corresponding values obtained in the lab during dual-task walking, as compared to usual walking. Still, gait performance during most daily-living walking bouts is worse than that measured during usual and dual-tasking in the lab. The values measured in the lab do not reliably reflect daily-living measures. That is, an older adult’s typical daily-living gait cannot be estimated by simply measuring walking in a structured, laboratory setting.

1 January 2014 in Journal of NeuroEngineering and Rehabilitation
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DTDiana Trojaniello
Diana Trojaniello
ANDREA CereattiANDREA Cereatti
ANDREA Cereatti
EPElisa Pelosin
Elisa Pelosin
LALaura Avanzino
Laura Avanzino
AMAnat Mirelman
Anat Mirelman
UCUgo Della Croce
Ugo Della Croce
The step-by-step determination of the spatio-temporal parameters of gait is clinically relevant since it provides an estimation of the variability of specific gait patterns associated with frequent geriatric syndromes. In recent years, several methods, based on the use of magneto-inertial units (MIMUs), have been developed for the step-by-step estimation of the gait temporal parameters. However, most of them were applied to the gait of healthy subjects and/or of a single pathologic population. Moreover, spatial parameters in pathologic populations have been rarely estimated step-by-step using MIMUs. The validity of clinically suitable MIMU-based methods for the estimation of spatio-temporal parameters is therefore still an open issue. The aim of this study was to propose and validate a method for the determination of both temporal and spatial parameters that could be applied to normal and heavily compromised gait patterns. Methods: Two MIMUs were attached above each subject's ankles. An instrumented gait mat was used as gold standard. Gait data were acquired from ten hemiparetic subjects, ten choreic subjects, ten subjects with Parkinson's disease and ten healthy older adults walking at two different gait speeds. The method detects gait events (GEs) taking advantage of the cyclic nature of gait and exploiting some lower limb invariant kinematic characteristics. A combination of a MIMU axes realignment along the direction of progression and of an optimally filtered direct and reverse integration is used to determine the stride length. Results: Over the 4,514 gait cycles analyzed, neither missed nor extra GEs were generated. The errors in identifying both initial and final contact at comfortable speed ranged between 0 and 11 ms for the different groups analyzed. The stride length was estimated for all subjects with less than 3% error. Conclusions: The proposed method is apparently extremely robust since gait speed did not substantially affect its performance and both missed and extra GEs were avoided. The spatio-temporal parameters estimates showed smaller errors than those reported in previous studies and a similar level of precision and accuracy for both healthy and pathologic gait patterns. The combination of robustness, precision and accuracy suggests that the proposed method is suitable for routine clinical use.