Evidence map›Paper›PMID 42834925›Full record

ArticleFrontiers in robotics and AI2026

Bridging stakeholder needs and technological capabilities to identify humanoid robot applications in rehabilitation: a case study in an ALS multidisciplinary care unit.

Rachele Piras, Samuele Bordini, Riccardo K Simi, Ilaria Consolo, Valentina Esposito, Claudia Cavaggion, Maddalena Feder, Maria Fossati, Giorgio Grioli, Antonio Bicchi and 2 more

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Rachele PirasIstituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation, Milano Institute, Milan, Italy.
Samuele BordiniCentro Di Ricerca E. Piaggio E Dipartimento Di Ingegneria Dell'Informazione, Università Di Pisa, Pisa, Italy.
Riccardo K SimiCentro Di Ricerca E. Piaggio E Dipartimento Di Ingegneria Dell'Informazione, Università Di Pisa, Pisa, Italy.
Ilaria ConsoloIstituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation, Milano Institute, Milan, Italy.
Valentina EspositoIstituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation, Milano Institute, Milan, Italy.
Claudia CavaggionIstituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation, Milano Institute, Milan, Italy.
Maddalena FederFraunhofer Italia - IEC Bolzano, Bolzano, Italy.
Maria FossatiSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Giorgio GrioliCentro Di Ricerca E. Piaggio E Dipartimento Di Ingegneria Dell'Informazione, Università Di Pisa, Pisa, Italy.
Antonio BicchiCentro Di Ricerca E. Piaggio E Dipartimento Di Ingegneria Dell'Informazione, Università Di Pisa, Pisa, Italy.
Christian Lunetta *Istituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation, Milano Institute, Milan, Italy.
Manuel G Catalano *Physical AI Technologies for Human-Robot Coevolution, Istituto Italiano di Tecnologia, Genova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of assistive service robots in healthcare has gained increasing attention for its potential to support clinical workflow and patient wellbeing. However, structured methodological approaches to identify clinically relevant applications for versatile robotic platforms before clinical implementation are still lacking. Moreover, the deployment of robots in these settings is often restricted to hyper-specialized tasks. To address these challenges, this study describes a stakeholder-driven process adopting a multidisciplinary co-design approach to adapt the Alter-Ego semi-anthropomorphic robot to the needs of a multidisciplinary neurorehabilitation unit for patients with Amyotrophic Lateral Sclerosis. We combined brainstorming, focus groups with healthcare professionals, patients and caregivers, and contextual observations to identify the real unmet needs and potential applications. The engineering team assessed the technological requirements and implementation readiness of each application. The clinical and engineering teams jointly reviewed the proposal, considering clinical, ethical, and infrastructural implications. This consensus-based process resulted in 12 use cases selected for the clinical protocol corresponding to 40 planned experimental sessions including autonomous or semi-autonomous tasks, as well as teleoperated activities for assistive and rehabilitation purposes. Furthermore, an exploratory pilot evaluated a subset of selected use cases, providing feedback to refine the platform and experimental protocol. Standardized assessments provided descriptive information on perceived workload, usability, and satisfaction. Participants generally reported a positive experience and manageable workload, while task-specific feedback identified aspects requiring further refinements. Overall, this experience offers preliminary insights into how clinical needs and technological capabilities can be jointly explored, providing a basis for subsequent clinical experimentation.

Indexed as

amyotrophic lateral sclerosisclinical translationhumanoid robotsrehabilitation and assistive roboticsstakeholder-driven design

Identifiers

PMID42834925
PMCPMC13634871

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.