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Abstract 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 .

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.

Timely and reliable identification of control phases is functional to the control of a powered robotic lower-limb prosthesis. This study presents a commercial energy-store-and-release foot prosthesis instrumented with a multimodal sensory system comprising optoelectronic pressure sensors (PS) and IMU. The performance was verified with eight healthy participants, comparing signals processed by two different algorithms, based on PS and IMU, respectively, for real-time detection of heel strike (HS) and toe-off (TO) events and an estimate of relevant biomechanical variables such as vertical ground reaction force (vGRF) and center of pressure along the sagittal axis (CoPy). The performance of both algorithms was benchmarked against a force platform and a marker-based stereophotogrammetric motion capture system. HS and TO were estimated with a time error lower than 0.100 s for both the algorithms, sufficient for the control of a lower-limb robotic prosthesis. Finally, the CoPy computed from the PS showed a Pearson correlation coefficient of 0.97 (0.02) with the same variable computed through the force platform.

Wearable robotic devices require sensors and algorithms that can recognize the user state in real-time, in order to provide synergistic action with the body. For devices intended for locomotion-related applications, shoe-embedded sensors are a common and convenient choice, potentially advantageous for performing gait assessment in real-world environments. In this work, we present the development of a pair of pressure-sensitive insoles based on optoelectronic sensors for the real-time estimation of temporal gait parameters. The new design makes use of a simplified sensor configuration that preserves the time accuracy of gait event detection relative to previous prototypes. The system has been assessed relatively to a commercial force plate recording the vertical component of the ground reaction force (vGRF) and the coordinate of the center of pressure along the so-called progression or antero-posterior plane (CoPAP) in ten healthy participants during ground-level walking at two speeds. The insoles showed overall median absolute errors (MAE) of 0.06 (0.02) s and 0.04 (0.02) s for heel-strike and toe-off recognition, respectively. Moreover, they enabled reasonably accurate estimations of the stance phase duration (2.02 (2.03) % error) and CoPAP profiles (Pearson correlation coefficient with force platform ρCoP = 0.96 (0.02)), whereas the correlation with vGRF measured by the force plate was lower than that obtained with the previous prototype (ρvGRF = 0.47 (0.20)). These results confirm the suitability of the insoles for online sensing purposes such as timely gait phase estimation and discrete event recognition.