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Background: In the context of post-traumatic hand rehabilitation, stiffness of the hand joints limits the range of motion (ROM), grip strength, and the possibility of performing simple grasps. Robotic rehabilitation has been widely adopted for hand treatment with neurological patients, but its application in the orthopaedic scenario remains limited. In this paper, a pilot study targeting this population is presented, where the rehabilitation is performed using a powered finger exoskeleton, namely I-Phlex. The device aims to mobilize the metacarpal-phalangeal joint (MCP) in flexion-extension movements. The objective of the study was to verify the short-term efficacy, experience of use, and safety of I-Phlex in a clinical setting. As a secondary objective, the study verified the device's capability to measure clinically relevant variables., Methods: Six subjects with trauma-related illnesses of the right hand took part in the experiment. Passive and active range of motion (PROM and AROM) were recorded at the beginning and the end of the session by the therapist and by the exoskeleton. Experience of use was assessed through ad-hoc questionnaires and a numerical pain rate scale (NPRS). Safety was assessed by computing the number of adverse events during the operation., Results: Median increases in the PROM and AROM of 5.88% and 11.11% respectively were recorded among subjects. The questionnaires reported a median score of 93.83; IQR (85.01-100) and 80.00; IQR (79.79-93.75) respectively. No increase in the median NPRS was recorded among subjects between pre-and post-treatment. No major adverse event or injury to the patients was recorded. Only one malfunction was reported due to the brake of a transmission cable, but the patient reported no injury or discomfort. No statistical significance was observed between the ROM measurement recorded using the exoskeleton and the ones taken by the therapist using the goniometer., Conclusions: The device and related rehabilitation exercises can be successfully used in the clinical rehabilitation of the MCP joint. The device measurements are in line with the goniometer assessment from the therapist. Future studies will aim to reinforce the results obtained, introducing a control group to conclude on the specific contribution of the technology compared to conventional therapy., Trial Registration: Hand Motor Rehabilitation Using a Wearable Robotic Device (WRL HX MCP), Clinicaltrials.gov ID NCT05155670, Registration date 13 December 2021, URL https://clinicaltrials.gov/ct2/show/NCT05155670 ., Competing Interests: Declarations. Ethics approval and consent to participate: This study was approved by the Ethical Committee of Area Vasta Nord Ovest (Tuscany, Italy) and all participants provided written informed consent. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The identification of personalized preventive strategies plays a major role in contrasting the occurrence of work-related musculoskeletal disorders. This requires the identification of distinct movement patterns within large samples and the attribution of a proper risk level to each identified movement phenotype. We assessed the feasibility of this approach by exploiting wearable inertial measurement units to estimate the whole-body kinematics of 43 healthy participants performing 18 reach-to-manipulate movements, which differed based on the object's position in the space and the type of manipulation required. Through unsupervised clustering, we identified multiple movement phenotypes graded by ergonomic performance. Furthermore, we determined which joints mostly contributed to instantiating the ergonomic differences across clusters, emphasizing the importance of monitoring this aspect during occupational gestures. Overall, our analysis suggests that movement phenotypes can be identified within occupational motor repertoires. Assigning individual performance to specific phenotypes has the potential to inform the development of more effective and tailored interventions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In the context of hand and finger rehabilitation, kinematic compatibility is key for the acceptability and clinical exploitation of robotic devices. Different kinematic chain solutions have been proposed in the state of the art, with different trade-offs between characteristics of kinematic compatibility, adaptability to different anthropometries, and the ability to compute relevant clinical information. This study presents the design of a novel kinematic chain for the mobilization of the metacarpophalangeal (MCP) joint of the long fingers and a mathematical model for the real-time computation of the joint angle and transferred torque. The proposed mechanism can self-align with the human joint without hindering force transfer or inducing parasitic torque. The chain has been designed for integration into an exoskeletal device aimed at rehabilitating traumatic-hand patients. The exoskeleton actuation unit has a series-elastic architecture for compliant human-robot interaction and has been assembled and preliminarily tested in experiments with eight human subjects. Performance has been investigated in terms of (i) accuracy of the MCP joint angle estimation through comparison with a video-based motion tracking system, (ii) residual MCP torque when the exoskeleton is controlled to provide null output impedance and (iii) torque-tracking performance. Results showed a root-mean-square error (RMSE) below 5 degrees in the estimated MCP angle. The estimated residual MCP torque resulted below 7 mNm. Torque tracking performance shows an RMSE lower than 8 mNm in following sinusoidal reference profiles. The results encourage further investigations of the device in a clinical scenario.

Background: Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors., Methods: PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used., Results: A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of -0.62 (95%CI - 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = -1.019, 95% CI - 1.827; -0.210, p -value = 0.0135)., Conclusions: RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy.