Dataset on gait patterns in degenerative neurological diseases

We collected the gait parameters and lower limb joint kinematics of patients with three different types of primary degenerative neurological diseases: (i) cerebellar ataxia (19 patients), (ii) hereditary spastic paraparesis (26 patients), and (iii) Parkinson's disease (32 patients). Sixty-five gender-age matched healthy subjects were enrolled as control group. An optoelectronic motion analysis system was used to measure time-distance parameters and lower limb joint kinematics during gait in both patients and healthy controls

An adaptive Cooperative Receding Horizon controller for the multivehicle routing problem

The objective of the Vehicle Routing Problem (VRP), in the meaning of this paper, is to find the best path for a vehicle, or the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Possible applications of the vehicle routing problem include surveillance, exploration, logistic, transportation, relief systems, etc. A lot of research has been carried out so far, but the VRP remains a complex and computationally expensive combinatorial problem, leading to the difficulty to actually solve the problem on-line. This paper presents a technique based on the Cooperative Receding Horizon (CRH) approach proposed in [Li06], in which a sequence of optimization problems are computed over a planning horizon and the decisions are applied only over a shorter action horizon, in order to rapidly adapt to possible configuration changes (e.g., new targets appearance). Moreover, the proposed algorithm is able to dynamically adapt to the time-variable configuration of both vehicles and targets as well as to handle the discovery of unknown targets. Several proof of concept simulations show the enhancements of the proposed technique in comparison to the one in [Li06]

Control strategies for the vehicle routing problem applied to medical emergencies

This thesis deals with dynamic Multi-Vehicle Routing Problem (MVRP) in both deterministic and stochastic scenarios. The objective of the MVRP is to find the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Based on the Cooperative Receding Horizon (CRH) approach proposed by Cassandras et al.(CRH) for the Euclidean case, this thesis: i) presents another algorithm that is more efficient with clustered targets (tCRH); ii) illustrates an algorithm that exploits CRH and tCRH strengths (aCRH); iii) extends CRH, tCRH and aCRH to realistic urban map case

Control strategies for the vehicle routing problem applied to medical emergencies

This thesis deals with dynamic Multi-Vehicle Routing Problem (MVRP) in both deterministic and stochastic scenarios. The objective of the MVRP is to find the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Based on the Cooperative Receding Horizon (CRH) approach proposed by Cassandras et al.(CRH) for the Euclidean case, this thesis: i) presents another algorithm that is more efficient with clustered targets (tCRH); ii) illustrates an algorithm that exploits CRH and tCRH strengths (aCRH); iii) extends CRH, tCRH and aCRH to realistic urban map case

Cooperative receding horizon strategies for the multivehicle routing problem

This paper deals with the dynamic Euclidean Multivehicle Routing Problem (MVRP) in both deterministic and uncertain scenarios. The objective of MVRP is to find the best paths for a fleet of vehicles that are cooperative to visit a set of targets. Based on the cooperative receding horizon (CRH) approach proposed in some previous works, which is vehicle-oriented, in this paper, we consider a target-oriented CRH, named tCRH, and then we propose a switching scheme, named sCRH, which is able to dynamically adjust the vehicle behaviors according to the time-varying configuration of both vehicles and targets, as well as to handle the situation with the appearance of unknown targets. The proposed sCRH counteracts the oscillation problem of CRH and improves the overall routing performances by adopting the advantages of both CRH and tCRH approach. Convergence results and simulation results are provided to validate the proposed approach

Control of a Back-Support Exoskeleton to Assist Carrying Activities

Back-support exoskeletons are commonly used in the workplace to reduce low back pain risk for workers performing demanding activities. However, for the assistance of tasks differing from lifting, back-support exoskeletons potential has not been exploited extensively. This work focuses on the use of an active back-support exoskeleton to assist carrying. Two control strategies are designed that modulate the exoskeleton torques to comply with the task assistance requirements. In particular, two gait phase detection frameworks are exploited to adapt the assistance according to the legs' motion. The two strategies are assessed through an experimental analysis on ten subjects. Carrying task is performed without and with the exoskeleton assistance. Results prove the potential of the presented controls in assisting the task without hindering the gait movement and improving the usability experienced by users. Moreover, the exoskeleton assistance significantly reduces the lumbar load associated with the task, demonstrating its promising use for risk mitigation in the workplace.Comment: submitted to 2023 IEEE International Conference on Rehabilitation Robotics (ICORR

Equivalent Weight: Connecting Exoskeleton Effectiveness with Ergonomic Risk during Manual Material Handling

Occupational exoskeletons are becoming a concrete solution to mitigate work-related musculoskeletal disorders associated with manual material handling activities. The rationale behind this study is to search for common ground for exoskeleton evaluators to engage in dialogue with corporate Health & Safety professionals while integrating exoskeletons with their workers. This study suggests an innovative interpretation of the effect of a lower-back assistive exoskeleton and related performances that are built on the benefit delivered through reduced activation of the erector spinae musculature. We introduce the concept of “equivalent weight” as the weight perceived by the wearer, and use this to explore the apparent reduced effort needed when assisted by the exoskeleton. Therefore, thanks to this assistance, the muscles experience a lower load. The results of the experimental testing on 12 subjects suggest a beneficial effect for the back that corresponds to an apparent reduction of the lifted weight by a factor of 37.5% (the perceived weight of the handled objects is reduced by over a third). Finally, this analytical method introduces an innovative approach to quantify the ergonomic benefit introduced by the exoskeletons’ assistance. This aims to assess the ergonomic risk to support the adoption of exoskeletons in the workplace

High-density surface electromyography allows to identify risk conditions and people with and without low back pain during fatiguing frequency-dependent lifting activities

Low back pain (LBP) is a leading cause of disability in the workplace, often caused by manually lifting of heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk of lifting activities. This study aims to verify that, during the execution of fatiguing frequency-dependent lifting, high-density surface electromyography (HDsEMG) allows the discrimination of healthy controls (HC) versus people with LBP and biomechanical risk levels. Fifteen HC and eight people with LBP performed three lifting tasks with a progressively increasing lifting index, each lasting 15 min. Erector spinae (ES) activity was recorded using HDsEMG and amplitude parameters were calculated to characterize the spatial distribution of muscle activity. LBP group showed a less ES activity than HC (lower root mean square across the grid and of the activation region) and an involvement of the same muscular area across the task (lower coefficient of variation of the center of gravity of muscle activity). The results indicate the usefulness of HDsEMG parameters to classify risk levels for both HC and LBP groups and to determine differences between them. The findings suggest that the use of HDsEMG could expand the capabilities of existing instrumental-based tools for biomechanical risk classification during lifting activities.</p