Giada Devittori

Last Name

Devittori

First Name

Giada

ORCID

0000-0002-4945-8034

Organisational unit

03827 - Gassert, Roger / Gassert, Roger

Show all metadata

Search Results

Publications 1 - 9 of 9

Health knowledge after stroke in Switzerland: a survey among health professionals on current practice and suggestions for the implementation of a technology-based educational program for stroke survivors
Devittori, Giada; Peduzzi, Mosè; Dinacci, Daria; et al. (2024)
BMC Health Services Research
Background It is estimated that 1 in 4 stroke survivors will experience a second stroke. Educating patients about risk factors for stroke and a generally healthier lifestyle may help prevent recurrent strokes, which are a burden on society and the healthcare system. The goals of this paper were to investigate the estimated level of knowledge of stroke patients regarding their disease, the methods of information commonly used in clinical practice, the topics that should be included in an educational program aimed at improving health knowledge among stroke survivors, and how such a program could be delivered with the help of technology-based education (i.e., information delivered by digital platforms such as smartphones or rehabilitation technologies). Methods We performed a survey among health professionals working with stroke patients in Switzerland. Results 161 health professionals of different backgrounds took part in the survey, and 94 completed it. According to the results, only 33% of healthcare professionals thought that patients were well informed about stroke one month after stroke onset. These findings suggest that there is room for improvement in how stroke patients are educated about stroke, risk factors, and prevention. Additionally, it was highlighted that technology is not commonly used in clinical practice to support patients’ education, although this is an acceptable method for healthcare professionals. The results also helped to identify key topics to be included in an educational program and recommendations for implementing such a program in rehabilitation technologies. Conclusions This work allowed gaining more insight into healthcare professionals’ opinions on the potential of technology-based education and key aspects to consider when implementing it to support health and prevention knowledge after stroke.
Towards RehabCoach: Design and Preliminary Evaluation of a Conversational Agent Supporting Unsupervised Therapy After Stroke
Devittori, Giada; Akeddar, Mehdi; Retevoi, Alexandra; et al. (2024)
2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Unsupervised therapy after stroke is a promising way to boost therapy dose without significantly increasing the workload on healthcare professionals. However, it raises important challenges, such as lower adherence to therapy in the absence of social interaction with therapists. We present the initial prototype of RehabCoach, a novel smartphone-based app with conversational agent to support unsupervised therapy. RehabCoach is designed to increase patients' engagement and adherence to therapy and to provide information (e.g., about stroke, health) in an interactive and user-friendly manner. We report on the design and usability evaluation of the first prototype of RehabCoach, assessed by four stroke patients and five healthcare professionals, who interacted with the app in a single testing session. Task completion time and success rates were measured for 15 representative tasks, and participants assessed usability via questionnaires and a semi-structured interview. Results show that it was feasible for stroke patients to successfully interact with RehabCoach (task success ≥93%) without requiring extensive training. Participants positively rated the usability of RehabCoach (mean mHealth App Usability Questionnaire score: 1.3 for primary users, 1.4 for healthcare professionals, on a scale from 1 (positive evaluation) to 7). The feedback collected in this work opens the door to further enhance RehabCoach as an interactive digital tool to support unsupervised rehabilitation.
Design Considerations and Pilot Usability Evaluation of ReHandyBot, A Portable Device for Upper Limb Therapy Along the Continuum of Care
Devittori, Giada; Ranzani, Raffaele; Song, Jaeyong; et al. (2025)
Biosystems & Biorobotics ~ Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024
Increasing the dose of therapy administered to persons after neurological injuries may improve their functional outcome. Unsupervised robot-assisted therapy is one possible approach to support therapy along the continuum of care without overloading the healthcare system. This work summarizes the design of ReHandyBot, an active, portable device for upper limb rehabilitation targeting unsupervised use in the clinic or at home. Additionally, its preliminary usability evaluation by four stroke subjects who used the device for two weeks is described. The results showed that ReHandyBot is a suitable platform for implementing quality robot-assisted exercises, and stroke patients could use it with minimal supervision, rating its usability as excellent (mean score for the System Usability Scale > 85). This pilot study opens the door to a larger study with ReHandyBot aiming at increasing therapy dose after stroke.
Unsupervised Robot-Assisted Therapy at Home After Stroke: a Pilot Feasibility Study
Devittori, Giada; Dinacci, Daria; Petrillo, Claudio; et al. (2025)
2025 International Conference On Rehabilitation Robotics (ICORR)
Unsupervised robot-assisted therapy could allow increasing upper limb therapy dose for stroke survivors with minimal additional burden on the healthcare system. Thanks to the ability to actively assist movement and dynamically adapt the assistance level, actuated devices can support individuals with a wide range of deficits. However, these devices are often complex to use, and their application in a fully unsupervised setting has rarely been explored. Here, we present a pilot study investigating the feasibility of unsupervised therapy with ReHandyBot, an actuated device for upper limb rehabilitation. The increase in therapy dose achieved during unsupervised training, device usability and user experience were evaluated. Stroke inpatients of a rehabilitation clinic learned how to use the device for two weeks with progressively decreasing levels of supervision. After discharge, they could take it home for two weeks of unsupervised therapy. Four of the five recruited participants learned how to use the device without supervision, and three completed the protocol. During the two weeks at home, on average they performed 518.3 minutes of therapy with ReHandyBot. Usability and user experience ratings show that the device was well accepted. These positive results support larger studies investigating unsupervised home therapy with ReHandyBot and suggest that active devices can be used by patients with no to mild cognitive impairments at home without the supervision of external persons.
Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience
Devittori, Giada; Dinacci, Daria; Romiti, Davide; et al. (2023)
Research Square
Background Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability. Methods Subacute stroke patients underwent a four-week protocol composed of daily 45 minutes-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were the primary outcome measures. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists’ absence. Results Unsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 minutes of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred. Conclusions We demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose.
Unsupervised Robot-Assisted Therapy: From the Clinic to the Home
Devittori, Giada (2024)
Stroke affects more than 12 million people every year. Many stroke survivors are left with upper limb impairments, which negatively impact their independence in daily life and their quality of life. Giving individuals after a stroke the opportunity to perform more upper limb therapy sessions than those offered during usual care might improve their functional outcomes and overall well-being. However, providing more therapy sessions (i.e., increasing the dose of therapy) to stroke patients, either during their stay in the clinic or at home after discharge, presents many difficulties. Indeed, the current rehabilitation model consists mainly of 1-to-1 supervised therapy sessions (i.e., one therapist treats one patient at a time). Following this model, increasing the therapy dose is not sustainable due to both the limited number of available therapists and the high costs associated with 1-to-1 rehabilitation. One approach that holds the promise of giving stroke patients access to more therapy while only adding a minimal burden on therapists and the healthcare system is unsupervised therapy. In this setting, patients perform exercises independently and without the supervision of any external person, ideally in the comfort of their home. Several tools to support unsupervised therapy have been explored, from booklets of conventional exercises to virtual reality-based exercises and robotic devices. Thanks to the ability to actively support movements, monitor patients' impairment, and provide engaging therapy, active robotic devices (i.e., actuated) appear to be the most comprehensive solution to support a wide range of stroke patients during unsupervised upper limb therapy. However, most active robotic devices do not meet the requirements to be used unsupervised by stroke patients. For instance, they are often difficult to use, not safe enough, or do not have the ability to automatically adapt the difficulty of therapy to the patient's level of impairment. Therefore, the unsupervised use of active robotic devices has rarely been explored, and developing active robotic devices that meet the requirements for unsupervised use is thus critical to provide patients with different impairment levels with additional quality therapy both at the clinic and home. This thesis aimed to evaluate if fully unsupervised upper limb therapy supported by an active rehabilitation robot is feasible and can increase therapy dose at the clinic and directly at the patients' homes. To do so, an existing upper limb rehabilitation platform (i.e., ReHapticKnob) that includes an active robotic device, the software that controls it, and exercises based on the concept of neurocognitive therapy was used as a starting point. The first step toward unsupervised use of ReHapticKnob was to identify, develop, and implement the necessary adaptations for the platform to meet the requirements for being used independently by patients. Then, a study protocol was developed to implement and comprehensively evaluate the transition from supervised to unsupervised use of the rehabilitation platform. The study protocol lasted about four weeks. During the first week, patients trained with ReHapticKnob under the supervision of a therapist, who explained how to interact with it. During the second week, a therapist was present but remained in the background and observed patients performing therapy with the platform independently, intervening only when necessary. If deemed capable of doing so, during the third and fourth weeks, patients were allowed to practice with ReHapticKnob unsupervised, always in the clinical setting. The updated version of ReHapticKnob was tested following this protocol in a pilot clinical study with 13 stroke inpatients of the Clinica Hildebrand centro di riabilitazione Brissago, of which 12 could train with the platform without supervision. The results, therefore, supported the hypothesis that it is feasible for stroke patients to learn to use a robotic technology independently and that unsupervised rehabilitation with it can lead to a meaningful increase in the therapy dose (i.e., + 40\%). In addition, the study participants positively evaluated the usability of ReHapticKnob and the user experience when training with it. The positive findings of this study motivated us to test the unsupervised therapy with ReHapticKnob in patients' homes. To do this, it was first necessary to develop a portable version of the platform, named ReHandyBot, as the original platform was too bulky to be moved and set up at home easily. Based on the experience gained during the first study, ReHandyBot was first designed in view of unsupervised use at the patient's home. Then, it was tested in a clinical study with stroke patients following a slightly modified version of the study protocol mentioned before. Patients could take ReHandyBot home after being discharged from the clinic to continue training with it for two weeks without any external supervision. The study is still ongoing, and when handing in this thesis, two patients could take ReHandyBot home. The patient who finished the protocol did almost 10 hours of therapy at home with the support of the rehabilitation platform, training with it daily and rating its usability as very high. Preliminary promising results suggest that our platform can also be used unsupervised at stroke patients' homes and that the dose of upper limb therapy for outpatients can be increased considerably. In parallel to this, this thesis explored various strategies to further enrich and exploit a platform for rehabilitation. This included the development of a prototype of a smartphone application to promote engagement during unsupervised rehabilitation. Additionally, an educational program aimed at improving patients' knowledge of stroke and general health was also developed and embedded in the therapy sessions performed with ReHapticKnob. Pilot evaluations of these strategies yielded positive results, supporting their further development and testing to provide an enriched experience that could further support and motivate patients during their rehabilitation journey. In conclusion, this work has shown for one of the very first times that active robotic devices for upper limb rehabilitation can be employed for fully unsupervised use, both in the clinic and at patients' homes. The findings of this thesis suggest that it is possible to increase the therapy dose through this therapy setting, which can be safe and well accepted by patients and lead to functional gains. This work paves the way for the unsupervised use of active robotic devices for upper limb rehabilitation, which allows for delivering more quality therapy for stroke patients than usual care without burdening the healthcare system excessively. This could ultimately improve the quality of life for people affected by stroke.
Progressive Transition From Supervised to Unsupervised Robot-Assisted Therapy After Stroke: Protocol for a Single-Group, Interventional Feasibility Study
Devittori, Giada; Ranzani, Raffaele; Dinacci, Daria; et al. (2023)
JMIR Research Protocols
Background: Increasing the dose of therapy delivered to patients with stroke may improve functional outcomes and quality of life. Unsupervised technology-assisted rehabilitation is a promising way to increase the dose of therapy without dramatically increasing the burden on the health care system. Despite the many existing technologies for unsupervised rehabilitation, active rehabilitation robots have rarely been tested in a fully unsupervised way. Furthermore, the outcomes of unsupervised technology-assisted therapy (eg, feasibility, acceptance, and increase in therapy dose) vary widely. This might be due to the use of different technologies as well as to the broad range of methods applied to teach the patients how to independently train with a technology. Objective: This paper describes the study design of a clinical study investigating the feasibility of unsupervised therapy with an active robot and of a systematic approach for the progressive transition from supervised to unsupervised use of a rehabilitation technology in a clinical setting. The effect of unsupervised therapy on achievable therapy dose, user experience in this therapy setting, and the usability of the rehabilitation technology are also evaluated. Methods: Participants of the clinical study are inpatients of a rehabilitation clinic with subacute stroke undergoing a 4-week intervention where they train with a hand rehabilitation robot. The first week of the intervention is supervised by a therapist, who teaches participants how to interact and train with the device. The second week consists of minimally supervised therapy, where the therapist is present but intervenes only if needed as participants exercise with the device. If the participants properly learn how to train with the device, they proceed to the unsupervised phase and train without any supervision during the third and fourth weeks. Throughout the duration of the study, data on feasibility and therapy dose (ie, duration and repetitions) are collected. Usability and user experience are evaluated at the end of the second (ie, minimally supervised) and fourth (ie, unsupervised) weeks, allowing us to investigate the effect of therapist absence. Results: As of April 2023, 13 patients were recruited and completed the protocol, with no reported adverse events. Conclusions: This study will inform on the feasibility of fully unsupervised rehabilitation with an active rehabilitation robot in a clinical setting and its effect on therapy dose. Furthermore, if successful, the proposed systematic approach for a progressive transition from supervised to unsupervised technology-assisted rehabilitation could serve as a benchmark to allow for easier comparisons between different technologies. This approach could also be extended to the application of such technologies in the home environment, as the supervised and minimally supervised sessions could be performed in the clinic, followed by unsupervised therapy at home after discharge.
Building Conversational Agents for Stroke Rehabilitation: An Evaluation of Large Language Models and Retrieval Augmented Generation
Retevoi, Alexandra; Devittori, Giada; Kowatsch, Tobias; et al. (2024)
IVA '24: Proceedings of the 24th ACM International Conference on Intelligent Virtual Agents
Conversational agents (CAs) have been successfully implemented to deliver digital health interventions. However, most of their applications focus on non-communicable diseases, e.g., diabetes. RehabCoach, a CA-based smartphone application designed to assist stroke survivors during at-home unsupervised rehabilitation, utilizes multiple CAs to deliver digital interventions for therapy adherence. Matthias, one of the CAs of RehabCoach, is a novel Large Language Model-based CA that leverages Retrieval Augmented Generation (RAG) to answer questions related to ReHandyBot, an upper limb rehabilitation device. In this work, we assessed the preciseness and conciseness of Matthias’s answers to 14 device-related questions. For each question, Matthias generated 6 answers, based on 3 different prompts and 2 different data sources, i.e., a conversational dataset containing dialogues about how to operate the device and the device manual of instructions. Results from a blinded evaluation performed by two device experts highlight that the responses of the CA generated using the conversational dataset were considered more concise (82,14%) and better overall (60,70%). This work shows the potential of using conversational data for device-assisted rehabilitation CAs deploying RAG.
Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience
Devittori, Giada; Dinacci, Daria; Romiti, Davide; et al. (2024)
Journal of NeuroEngineering and Rehabilitation
Background Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability. Methods Subacute stroke patients underwent a four-week protocol composed of daily 45 min-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were evaluated. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists' absence. Results Unsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 min of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred. Conclusions We demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose. These results support the application of unsupervised robot-assisted therapy as a complement to usual care in clinical settings and pave the way to its application in home settings.

Publications 1 - 9 of 9

Giada Devittori

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results