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Movendo Technology

Clinical Studies

Movendo Technology is a medical company that develops innovative and easy-to-use rehabilitation solutions thanks to the use of the most advanced robotic technology.

Movendo Technology operates worldwide, with a dedicated clinical team resident at MT headquarters, focused on facilitating collaborations with the Movendo clinical international network. MT clinical team collaborates with all its partners for data collection and data analysis and for thecreation of literature and scientific evidence.

Objective evaluation and scientific approach are part of the innovation at the core of Movendo DNA, and are combined with machinelearning and Artificial Intelligence to create new solutions for rehabilitation and diagnostics.


Meet our clinical team

VALENTINA SQUERI

Clinical affairs & product development manager

Graduated in biomedical engineering at the University of Genova, Genova, Italy, in 2004, with a thesis concerning the analysis of upper arm’s movements in patients with hemicrania and received the M.S. degree in bioengineering from the University of Genova, in 2006, studying the development and validation of a robot therapy rehabilitation protocol for patients with Multiple Sclerosis. In 2010 she received the Ph.D. degree in humanoid technologies from the University of Genova, with a thesis concerning how to use robots to study sensorimotor performance and promote neuromotor recovery. From 2010 to 2016, she worked as Post Doctoral Researcher at the Italian Institute of Technology (IIT), Genova. The scientific aim of her research was to investigate with robotic devices the neural control of movements and motor learning mechanisms, with the technological goal of develop robots and algorithms that can support and optimize rehabilitation. During her scientific carrier she published papers on peer-reviewed journals. She works currently as Clinical affairs and product development manager in Movendo Technology.

ALICE DE LUCA

Clinical projects coordinator

Graduated in biomedical engineering in 2008 at University of Genoa and received the M.S. degree in bioengineering in 2010 from the University of Genoa. In 2016 she received the PhD degree in bioengineering from the University of Genoa with a research project focused on rehabilitation and compensatory strategies in stroke and spinal cord injury survivors. From 2011 to 2016 she worked in the Rehabilitation Department of the Santa Corona Hospital with a specific activity related to motion analysis and robotic rehabilitation in neurologic field. Since 2017, Alice is working in Movendo Technology as part of the product development and clinical application team and is currently in charge of coordinating the activities related to clinical projects.
She is author and co-author of many publications on peer-reviewed journals.


Design and Development of a Novel Core, Balance and Lower Limb Rehabilitation Robot: hunova®

This article describes the technical aspects at the basis of the development of hunova®.
The robot design has been described in detail, starting from the hardware mechanisms, the system electronic and control components as well as the software. hunova® has been ergonomically designed to maximize the number of the possible rehabilitation exercises and evaluations, in all areas
as neuro, ortho, geriatrics and sport.
hunova® allows to measure significant parameters of static and dynamic stability and can centralize a complex progression of exercises to recover trunk control and reactive balance after traumaticinjuries.


Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults

Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many falls are preventable, the early identification of older adults at risk of falling is crucial in order to develop tailored interventions to prevent such
falls. To date, however, the fall-risk assessment tools currently used in the elderly have not shown sufficiently high predictive validity to distinguish between subjects at high and low fall risk.
Consequently, predicting the risk of falling remains an unsolved issue in geriatric medicine. This one-year prospective study aims to develop and validate, by means of a cross-validation method, a multifactorial fall-risk model based on clinical and robotic parameters in older adults.


Robotic balance assessment in community-dwelling older people with different grades of impairment of physical performance

Impaired physical performance is common in older adults and has been identified as a major risk factor for falls. To date, there are no conclusive data on the impairment of balance parameters in older subjects with different levels of physical performance. The aim of this study was to investigate the relationship between different grades of physical performance, as assessed by the Short Physical Performance Battery (SPPB), and the multidimensional balance control parameters, as measured by
means of a robotic system, in community-dwelling older adults.


Effect of a robotic training focused on balance and core stability in Parkinson’s disease: a pilot study

In Parkinson’s disease, rehabilitation aims to improve patients’ quality of life by promoting their independence, safety and well-being. To achieve these goals, rehabilitation first aims to prevent and/or delay inactivity, fear of moving or falling and to maintain and enhance physical capacity; as the disease progresses, the goal becomes to improve transfers, posture, balance, walking and functional gestures. The aim of this pilot study is to verify the feasibility and effectiveness of an integrated traditional-robotic rehabilitation treatment in Parkinson’s disease patients, using hunova, a robotic device developed for the rehabilitation of lower limbs and trunk.


Robot-based assessment of sitting and standing balance: preliminary results in Parkinson’s disease

Postural responses to unstable conditions or perturbations are important predictors of the risk of falling and can reveal balance deficits in people with neurological disorders, such as Parkinson’s Disease (PD). However, there is a lack of evidences related to devices and protocols providing a comprehensive and quantitative evaluation of postural responses in different stability conditions.


Dynamic Stability and Trunk Control Improvements Following Robotic Balance and Core Stability Training in Chronic Stroke Survivors: A Pilot Study.

Stroke survivors show greater postural oscillations and altered muscular activation compared to healthy controls. This results in difficulties in walking and standing, and in an increased risk of falls.
A proper control of the trunk is related to a stable walk and to a lower falling risk; to this extent, rehabilitative protocols are currently working on core stability. The main objective of this work was to evaluate the effectiveness of trunk and balance training performed with a new robotic
device designed for evaluation and training of balance and core stability, in improving the recovery of chronic stroke patients compared with a traditional physical therapy program.


A robot-based assessment of trunk control in Spinal Cord Injured athletes

Spinal Cord Injury (SCI) affects trunk control and determines altered or absent neuromuscular activity and sensory feedback below the lesioned spinal segment. The practice of sport or of any physical activity are key elements for improving the health and quality of life of people with SCI. Paralympic athletes overcome limits related to their injuries, achieving high neuromuscular control and coordination. Among the sports that have been adapted for people with disabilities, sit-skiing is a sport that requires good trunk control. However, there is a lack of instruments and protocols for its quantitative assessment. In this work we describe a robot-based protocol designed to assess trunk control and tested with two expert sit-skiers and eight unimpaired subjects.


The use of the robotic device hunova as rehabilitation and evaluation tool for functional balance in individuals with spinal cord injury

Postural control is a very important and basic requirement in daily human life. The robotic device hunova allows to evaluate and practice postural control using different exercises both in upright stance and seated position. While most functional tasks are not isolated to the trunk, the ones that challenge balance and sitting postural control require a high level of trunk control. When trunk control is impaired the development of less effective compensatory strategies is required.
Impaired trunk control functional implications are most evident in neurological conditions such as spinal cord injury. This study aims to investigate the use of hunova for the assessment and training of SCI subjects.


Ankle rehabilitation using the high-performance robotic device ARBOT 1 : results from a randomised controlled trial

Little is known about the effects of robotic training in orthopaedic conditions. A pilot study has been conducted in the INAIL Rehabilitation Center using ARBOT, a prototypal robotic system for ankle rehabilitation that consists of a 2-DOF electromechanical platform able to perform most of
the exercises foreseen by the standard rehabilitation programs. The aim of the study was to compare a traditional and a robotic aided rehabilitation training after ankle injuries.


Proprioceptive and motor training using the high-performance robotic device hunova: preliminary results of a randomized, controlled trial in patients with lower limb post-traumatic conditions

Lower limb trauma can cause kinetic chains impairments that compromise quality of movement and postural stability. A pilot study was conducted in INAIL Rehabilitation Center of Volterra using hunova, a robotic system for lower limbs and core stability training and evaluation, to examine whether robot assisted therapy is effective in motor control and gait performance recovery when compared to conventional rehabilitation programs.


Evaluation and rehabilitation training with hunova robotic system for the recovery of dynamic postural stability: open randomized interventional protocol, on patients after ACL surgical reconstruction

The anterior cruciate ligament (ACL) is strongly stressed during sports activity and is subject to frequent rupture events, often followed by a reconstruction surgery. The purpose of a rehabilitation program, after such an intervention, is to recover the range of movement, strengthen the musculature of the affected limb and stimulate the proprioceptive system, to bring the limb back to similar performance to those prior to the injury. The personalization of the rehabilitation after a ACL reconstruction is fundamental for both a conservative or accelerated approach. For this reason, the purpose of this work is to evaluate the effectiveness of a rehabilitative path mediated by hunova, able to provide, both in static and dynamic conditions, a precise evaluation of performance in terms of stability and balance in both bipodal and monopodalic standing. In addition, in the present work, hunova has been tested as a tool for proprioceptive, neuromotor and muscle strengthening training. The results of the assisted robot treatment are compared with those of the treatment conventionally provided by the structure.


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