Robotics and Neuroprosthetics for Rehabilitation

Study of the impact of a Robotic Therapy in Children with autism

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Fondazione Don Gnocchi
Instituto Superior Técnico – Universidade de Lisboa

Aim
Autism still does not have any cure. Several therapies have been developed for example using robots but their impact is still not clear. This project has a double aim: from one side, the quantitative analysis of a Pilot Study done with a Robotic Therapy and from the other side, the quantitative analysis of a Randomized Controlled Trial, with an improved version of the Robotic Therapy.

Project Phases:

• Literature review of the quantitative measures used in Robotics for Autism
• Analysis of the attention and movement of the subjects during the Pilot Study Data Acquisition in the Randomized Controlled Trial
• Relation between the two analysed measures and the clinical measures

Requirements:

• Motivation to interact with the therapists
• Good Programming skills: Python and Matlab

Design and test of control solutions for upper limb exoskeleton

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Prof.  Marta Gandolla – Dipartimento di meccanica

Aim:

Motorized upper limb exoskeletons have been proposed to support motor rehabilitation and/or to assist disabled people during daily life activities. We have developed and tested a 4DOF upper limb exoskeleton – AGREE. The thesis is aimed at developing and testing control solutions for the support of rehabilitation sesions (i.e., tunneling, force fields, assisted-as-needed solutions, synergy-based control, etc.)

Project phases:

• Literature Review
• Design of the control solution
• Implementation of the control solution on the AGREE platform
• Pilot tests of the developed control solution.

Requirements:

• Basic knowledge of Robotics​
• Good knowledge of C/C++ and MATLAB​
• Interest in learning ROS/MoveIt

Service robotics in nursing home: applications for elderly care

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Luca Pozzi (luca.pozzi@polimi.it)

Prof.  Marta Gandolla – Dipartimento di meccanica – DMec

Aim:
The rapidly growing demand for long-term care will become a hard challenge for the healthcare system. An investigation of the unmet-needs of nursing homes and the possible use-cases for a service robot, highlighted the following main areas of focus:
(i) communication and socialization;
(ii) cognitive stimulation and entertainment;
(iii) physical activity and rehabilitation.
In this context, the student activity will consist in the design, implementation and testing of service robot software applications (or new features for existing applications), addressing one or more of the identified area of focus. The activity will be based at the inter-dipartimental WE-COBOT  (Wearable and Collaborative Robotics) lab in Lecco.

Project phases:

After studying the state of the art, the application will be designed, implemented, and tested, possibly in a relevant environment and/or with end-users.

Requirements:

• Knowledge of Python.
• Basic knowledge of robotics.
• Basic knowledge (or willingness to learn) of ROS and Git/Github are welcome.

Adaptation and personalization in Human-Robot Interaction

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Luca Pozzi (luca.pozzi@polimi.it)

Prof.  Marta Gandolla – Dipartimento di meccanica – DMec

Aim:
In order to maximize acceptance, robots need to be acknowledged by people as natural partners. It is therefore essential for robots adapt their behavior to the one of their human interlocutor. This might be critical towards service robots usabilty in long-term care facilities for elderly and disabled people. In this context, the student will design and implement optimization algorithms to control the robot behavior and its adaptation to the user feedback (either explicit –questionnaires- or implicit –biosignals, gesture, face expression, body posture-). The activity will be based at the inter-dipartimental WE-COBOT  (Wearable and Collaborative Robotics) lab in Lecco.

Project phases:

After a thorough study of the state of the art, the optimization algorithm will be designed and implemented. The robot adaptation capability will then be tested in a use case relevant in the service/assistive robotics field.

Requirements:

Knowledge of Python. Basic knowledge of robotics. Basic knowledge (or willingness to learn) of ROS and Git/Github are welcome

Evaluation of a exoskeleton-mediated therapy: RCT study

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Prof.  Marta Gandolla – Dipartimento di meccanica.
Casa di Cura del Policlinico «Dezza»

Aim:
We have conducted a RCT study with the AGREE exoskeleton – an upper limb motorized 4DOF exoskeleton with neurological patients at Casa di Cura del Policlinico Dezza. We have collected instrumental and clinical data and outcome measures, which need to be processed to evaluate the effectiveness of the inclusion of the robotic-based therapy with respect to the standard care alone.

Project phases:

• Literature Review
• Familiarization with the AGREE system and the protocol
• Data analysis and interpretation

Requirements:

• Basic knowledge of Matlab

Benchmarking of upper limb functions in neurological disorders

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Prof.  Marta Gandolla – Dipartimento di meccanica.
Hospial Los Madronos (Madrid)

Aim:
We have developed a benchmarking scheme to evaluate upper limb functions in neurological disorders, and we have tested it on a group of healthy subjects. The scheme foresees a protocol and a list of relevant outcome measures. So that the scheme is effectively useful in the clinical context, this project wants to develop an application that guides the acquisition, data analysis and interpretation.

Project phases:

• Literature Review
• Familiarization with the benchmarking protocol
• Application development and verification
• Usability tests

Requirements:

• Basic knowledge of Matlab/C++

Aim 

Robot-assisted treadmill training is an established intervention used to improve walking ability in patients with neurological disorders. Usually, studies investigate biomechanical engagement during training and assess the efficacy of the intervention. On the other hand, the mental state and wellbeing is rarely considered but is a key factor in successful rehabilitation. New wearable devices, such as smartwatches, are able to continuously record physiological data during activities. The aim of this work is to assess the mental states of children during robot-based rehabilitation.

Expected Project Development 

• Data collection from E4 (Empatica)
• Development of algorithms to derive mental states from available sensors and correlate with psychological questionnaires
• Data analysis

Required skills 

• Knowledge of Matlab
• Interest in machine learning

Integrating Functional Electrical Stimulation in an upper limb exosuit: a hybrid approach

Elena Bardi
Davide Savona

Aim:
In the context of rehabilitation and assistance, soft exoskeletons (exosuits) represent a promising technology. Nevertheless, the rehabilitative potential of such devices could be boosted with the integration of FES (Functional Electrical Stimulation). The aim of the thesis is to integrate FES in an exosuit for the upper limb and to develop a hybrid control strategy.

Project phases:

• Literature Review on exosuits and FES-hybrid robotic systems
• Familiarization with the exosuit and the FES stimulator software
• Integration of FES in the exosuit control unit
• Development of a hybrid control strategy
• Usability study
•  

Requirements:

• Good knowledge in programming (Python, C++)

Optimization and testing of a hybrid robotic system for walking in Spinal Cord Injury people

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)
Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Villa Beretta Rehabilitation Center (Costa Masnaga, LC)

Aim:
In the last ten years, hybrid robotic systems, combining Functional Electrical Stimulation (FES) and exoskeletons, have been proposed to support locomotion in Spinal Cord Injury (SCI) people. Inside the FES-Leg project, in collaboration with INAIL, the two technologies were combined following a cooperative control strategy that integrates the torque produced by the motors with the residual effort of the subject as well as with the contribution provided by FES. 

The aim of the project is to optimize the control strategy and to support the testing of the system, both during preliminary tests on healthy subjects and during the clinical study (at Villa Beretta clinic) on SCI and stroke patients. 

Project phases:

• Literature Review
• Familiarization with the system
• Support during testing and data analysis

Requirements:

• Experience in programming (C++)

Dry textile electrode for Functional Electrical Stimulation applications

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)
Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

Ing. Paolo Perego
Dott. Roberto Sironi, Dipartimento di Design, Politecnico di Milano

Aim:
The use of Functional Electrical Stimulation in rehabilitation has increased over the years, in combination with movements such as cycling and walking with exoskeletons.

One of the main issues that still limits the usability of this technology is its limited wearability due to the use of adhesive electrodes that need to be accurately positioned. 

One interesting opportunity is the use of dry textile electrodes that could be integrated inside clothes and thus ease the processes of donning on and off. 

The aim of this project is to test the feasibility of textile electrodes for FES and to realize a wearable garment integrating FES and possibly EMG electrodes. 

Project phases:

• Literature Review
• Feasibility study
• Realization of a garment with textile electrodes

Requirements:

• Experience in programming (C++)
• Knowledge of Matlab (for data analysis)

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)
Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

INAIL Centro Protesi
Istituto Eugenio Medea

Aim:
Cycling by means of Functional Electrical Stimulation (FES) represents a well-known rehabilitation solution in neurological patients and a leading example of “Sport Therapy”, since cycling can be maintained for reasonably long periods, maximizing activity dependent neuroplasticity and can provide an accessible form of exercise for people with disabilities, favoring social inclusion and more engaging rehabilitation sessions.
Within the project FESleg, we are currently running a clinical study which aims at assessing the effects of a prolonged use of FES-cycling in 5 SCI people. The study aims at comparing outcome measures on autonomous system, muscle composition (via MRI), bladder activity, osteoporosis, and spasticity level, before and after a six-months treatment. Moreover, information acquired from the system (i.e. power output, resistance to fatigue) are evaluated to validate different stimulation strategies, to determine the patients’ improvements and to compare the effect of different stimulation frequencies.

Project phases:

• Literature review
• Data collection and assistance to weekly training with pilots
• Data analysis and interpretation

Requirements:

• Knowledge of Matlab

Intention detection strategies for hybrid FES-robot rehabilitation system

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)

Federica Ferrari (federica.ferrari@polimi.it)
Beatrice Luciani (beatrice.luciani@polimi.it)

Prof. Marta Gandolla – Department of Mechanical Engineering, Politecnico di Milano (DMEC)

Aim:
Upper limb Hybrid rehabilitation systems arise from the combination of exoskeletons and Functional Electrical Stimulation (FES) and are thought to assist goal-oriented rehabilitation tasks in patients with upper-limb weakness or hemiparesis following neurological disorders.
Such systems offer a viable solution to assist repetitive movements, but they usually provide passive assistance, excluding the active participation of subjects, which strongly enhances rehabilitation efficacy. 
Thus, the aim of this thesis is to develop Intention Detection algorithms based on machine learning models, to extract users’ intent to control the hybrid robotic system in order to enhance the active and voluntary participation of patients during the rehabilitation training so as to enhance rehabilitative outcomes. 

Project phases:

• Literature review
• Design of the control
• Validation tests

Requirements:

• Experience in programming in C++/Python
• Knowledge of Matlab

Study of the effects of Foot-Transmitted Vibration on the standing balance

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)
Prof. M. Tarabini

Dr. Flavia Marrone
Dr. Carlotta Massotti

INAIL
ISO (Intenational Organization for Standardization)

Aim:
The thesis aims at understanding the alteration of balance deriving from the exposure of standing subjects to vibration with different amplitude, frequency, and direction.

Project phases:

• Design of experiments (identification of vibration levels and frequencies, recruitment of participants)
• Tests @ Human Vibration Laboratory in Lecco. Tests will be performed on unique experimental facilities directly by the candidate, under the supervsion of the Lab personnel
• Data analysis and statistics
• Presentation of results during ISO meetings

Requirements:

• Basic knowledge of Matlab and/or python
• Knowledge of statistical software (Minitab, SPSS)
• MSc degree in biomedical or mechanical engineering
• Positive attitude towards experimental activities

Alteration of posture and muscular activity when using hand-held power tools on workers of different ages

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)
Prof. M. Tarabini

Dr. Flavia Marrone
Dr. Carlotta Massotti

INAIL
ISO (Intenational Organization for Standardization)

Aim:
The thesis aims at understanding how people of different age uses hand-held power tools (chainsaws and pneumatic hammers) with the aim of defining new vibration exposure limit value for workers.

Project phases:

• Design of experiments (identification of test population with university of Trieste, definition of the measurement chain, implementation of algorithms for data analysis)
• Tests on field (Trieste)
• Data analysis

Requirements:

• Basic knowledge of Matlab and/or python
• Knowledge of statistical software (Minitab, SPSS)
• MSc degree in biomedical or mechanical engineering
• Positive attitude towards experimental activities

OpenPose to OpenSim for large-scale injury mechanics reconstruction in team sports

Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it)

Prof. Matteo Zago

Università degli studi di Milano, Dipartimento di Scienze Biomediche per la Salute

Aim:
reconstruct athletes’ motion from TV coverage using advanced deep learning algorithms and computer vision techniques, such as pose estimation and motion tracking, and (2) use these information to estimate full body kinematics within OpenSim.

Project phases:

1. State of the art and background knowledge acuisition
   2. Data collection: acquire injury video dataset
2. Establish a computer vision system
3. Exporting motion in OpenSim
4. Results appraisal and evaluation

Requirements:

• Basics of Python required (TensorFlow or Keras) & AI
• Interest in sports tech
• Better in pair

ParkAGILE: Valutazione cinematica ed elettromiografica di protocolli fisioterapici di movimento per il benessere muscolare dei lavoratori digitali

Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it)

ParcAGILE è un attrezzo fisioterapico, compatto e completo, in grado di prevenire e riabilitare il disturbo muscolo scheletrico di origine professionale.
Un sistema unico e innovativo che consente di eseguire, nelle pause fisiologiche di lavoro, movimenti defaticanti, di allungamento muscolare e di mobilità delle articolazioni principalmente coinvolte dalle attività lavorative.

Aim:

Valutazione cinematica ed elettromiografica necessaria ad ottenere dei feedback di efficacia sull’uso del dispositivo ParcAGILE.

Ad integrazione, si ipotizza la realizzazione di un’applicazione che consenta all’utente di svolgere in autonomia una serie di programmi fisioterapici utilizzando ParcAGILE.