Technological innovation and changed perspectives on the value of work and workers are constantly changing our job profiles. The talk focuses on two innovations: powered exoskeletons and AI, which are set to change how we will work in the future. Rather than replacing us, robotic exoskeletons will apply AI to augment us more effectively and increasingly compensate our physical limitations – also helping to ensure workforces remain relevant and healthy for longer. Combining robotic strength and endurance with human intelligence, AI-powered exoskeletons provide an alternative to full automation. The talk will examine the 4 stages of AI implementation: learning, understanding, predicting & informing; to demonstrate how AI & powered exoskeletons will play together to become fully-fledged workplace safety assistants for everyone.

Industrial exoskeletons have recently gained importance as ergonomic interventions for physically demanding work activities. Due to the growing demand for exoskeletons, there is a need for new knowledge on the effectiveness of these systems. The EXOWORKATHLON®, as a prospective study approach, aims to assess exoskeletons in realistic use cases and evaluate them neutrally as a whole. For this purpose, three realistic Parcours and corresponding assessment methods were defined and have been carried out since then. The three defined Parcours so far include realistic use cases from logistics, automotive assembly, and welding. The study approach, the Parcours, and the assessments will be presented, including the latest results.

Robot-assisted gait training (RAGT) is a rehabilitation tool for gait refinement of individuals with neurological disabilities, especially of children with cerebral palsy (CP). The effectiveness of the therapy is linked to the patient's participation during the treatment, which is mainly due to her/his emotional state. This study investigates functional plasticity by functional near infrared spectroscopy and the psychophysiological state in children with CP using thermal infrared imaging. The results showed that RAGT produces changes in brain activity in both the motor and frontal cortex and an increase in the skin's thermal response as the sessions progress, thus suggesting an improvement in the child's motor control and attention during the gait, accompanied by an increase in participation and acceptance of therapy.

Recent technological improvements, particularly in mechatronic systems and materials, have advanced the development of lower limb exoskeletons. However, efficient use requires autonomous adaptation, predicting the user's intended motion and biomechanical changes in lower limb joints, i.e., position and torque estimation. For that purpose, recent studies have focused on using electromyography (EMG) signals. By utilizing time and frequency domain features extracted from EMG signals as input, deep and machine learning-based architectures, e.g., artificial neural networks, support vector machines, have showed to be efficient for accurate predictions. Nevertheless, proposed structures can be improved, serving commercialized product adaptation. Within this context, feature extraction and EMG implementation methods require further research studies in order to achieve reduced computational complexity and real-time applicability.

The objective of the work was to integrate a hybrid wearable that could facilitate physical tasks, and also, that could analyze and alert on risks associated to the development of the tasks. After an ergonomics characterization of workstation, a benchmarking of exoskeletons and sensors, and a review of ergonomic analysis methods: EXOSOFT and Xsens dot sensors were selected and integrated. The methodology of risk assessment selected was the OWAS methodology. A mobile application was created, allowing to have a real time feedback of postures and their risk associated. Also, a validation of the system was carried out: 4 users were measured EMG and MoCap at the laboratory, and 10 users measured in real conditions. A subjective questionnaire was also conducted.

There is growing interest to use soft robotic hands for prosthetic purpose due to their low-lost, light-weight, and safe interaction compared to current prosthetic hands based on rigid robotics. Our soft robotic prosthetic hands are 3D-printable with monolithic structures and integrated with soft sensors as part of their mechanical structure. The integration of soft sensors enables direct transition between different hand gestures, which greatly differs from the commercial hands requiring a neutral position (generally hand-opening) before starting a new gesture. Compared to sEMG, pressure-based FMG sensors (patent pending) are advantageous in decoding user intention from muscle activities due to low cost, stable signals, less signal processing, and light-weight. Together with a pFMG-based pattern recognition system, our hands will provide more intuitive and robust control for prosthetic hand users.

Industrial exoskeletons present a potential solution to reduce musculoskeletal disorders (MSD) and the risk of injury at work. Researchers and developers face design challenges to optimize the exoskeleton performance when the user interacts with it. In particular, active industrial exoskeletons introduce a challenge for developers since users must have control of certain domains in the exoskeleton. This academic talk presents the research, design and evaluation of a Human Machine Interface (HMI) called User Command Interface (UCI), this is an enhancement solution to adapt exoskeleton systems variability between tasks and users. The system can solve current interaction problems among developers and users such as secure identification, parameter configuration, signal visualization and storage for user specifications.

A wearable soft-robotic glove, Carbonhand, was tested for its potential effect on hand function when using it as assistive device. We coordinated a multi-center study to provide input to the manufacturer for CE certification under MDR. People with reduced grip strength used the glove at home for 6 weeks, with assessments of hand function, strength, user experience and quality of life before and after glove use. Interim results (n=46) showed that grip strength and hand function improved after glove use, and maintained up and until 4 weeks post-intervention, with positive user experience. It also gave rise to useful input for system improvements. This is promising for extending rehabilitation into people's homes, while offering assistance during daily activities.

This presentation delves into the application of engineering involving the integration of robotics, automation, and AI to automate life sciences experiments. We propose the utilization of AI methods within a robot-assisted platform for generating three-dimensional tumor tissue models. Recent technological advancements and innovative engineering solutions have the potential of standardization of the automatic production of the models. Offering flexibility in adjusting various experimental parameters. Manually analyzing such data is time-consuming and subject to inaccuracies stemming from individual subjectivity. Hence, there is a compelling need for a robust and efficient solution to evaluate the morphology of these models. Particularly for quality assessment and assessing therapeutic effects for individualized patient therapy.

Children with Cerebral Palsy (CP) mainly suffer from reduced quality of life resulting from diminishing mobility and independence. Recent studies have shown that Lower-limb Exoskeletons (LLEs) have significant potential to improve the walking functionality of children with CP. We developed a 6-DOF LLE, KAROL, with actuated joints in the knee, hip frontal, and hip sagittal. Human gait in LLE has highly unstable dynamics similar to the extremely unstable inverted pendulum. Hence, a control structure is highly desirable to stabilise human-LLE interaction. Furthermore, individuals with CP have more metabolic consumption than unimpaired peers, with gravity significantly contributing to this issue. Therefore, this study designed a model-based gravity compensator impedance controller for KAROL to mitigate the negative impact of gravity on this assistive technology.

The presentation will describe the SPINExo device: SuPport INdustrial opErators Exoskeleton, a back-support exoskeleton (developed by IDSIA USI/SUPSI and Politecnico di Milano). The proposed device allows to relieve the load applied to the backbone of the user while executing working activities, enhanced by its novel spine-based kinematics. Two versions of the device are available: a passive one and an actuated one. The passive device will be analyzed in the presentation, highlighting its main design features. The kinematics of the exoskeleton is scalable and customizable based on the specific user, adapting to the target subject’s back motion. The experimental test and validation of the device have been financed by the EUROBENCH project, under the XSPINE project. The presentation will show both the novel design of the prototype, together with the achieved results during the evaluation phase.

The SafeLegs is a supportive lower-limb 6-DOF exoskeleton demonstrator equipped with safety features. It is the result of collaboration between Uni Stuttgart and KIT. It consists of six actuators - brushless motors in the hips, knees, and ankles. Sensor signals are providing feedback from the motor encoders to the main system controller via the CAN bus. The SafeLegs is a complex Cyber-Physical System with components that prone to heterogeneous faults. To ensure safety we proposed a Deep Learning-based approach for system failure prevention. We employed LSTM network for error detection and mitigation. Trained LSTM models were quantized and deployed on an Edge TPU. The light weight of the system and minimal power consumption allowed its integration into wearable robotic systems.

The health of patients has increasing concerns in the sector motivating the appearance of powered lower and upper limb devices for human enhancement. The project "SMART-HEALTH-4-ALL | Smart medical technologies for better health and care", specifically the PPS2 – Personal Health Devices, aims to develop innovative solutions for patients with diabetic diagnosis and arm musculoskeletal rehabilitation applying ergonomic standards, active feedback, and a challenging level of technology integration. The smart shoe will be capable of mapping 3D plantar pressures and promote arterial stimulation through controlled vibration in plantar region of patients suffering from diabetic foot syndrome. Additionally, a textile sleeve with flexible electromyography sensors, control electronics, and gamification software has been prototyped, monitoring the upper and forearm muscles strengthening during rehabilitation.

The Group of Biomechatronics at the Technische Universität Ilmenau is developing an active exoskeleton for the upper extremity - especially the elbow joint. It is supposed to serve as a a scientific plattform to show the capabilties of exoskeleton technology to prevent musculoskeletal diseases in industrial applications like assembly. Main aspects of the development are a cost-effective design to make exoskeleton technology available for a broader number of users, a user-oriented design and the use of concepts from biorobotics and biomechatronics. Inspired by the biological paragon, the exoskeleton is driven by two antagonistic actuators. Compliant elements are used to increase biocompatibilty and user safety. To achieve an adjustable stiffness of the joint with the antagonistic principle, components with a nonlinear characteristic are needed. In this presentation, the current status of the development of actuation and compliant, nonlinear elements will be explained.

Wearable robotics (WR) are showing outstanding improvements in technical features, but their daily life usability is often limited. A core issue is a lacking understanding of the term usability, leading to a scattered landscape of definitions and evaluation methodologies to address the essential design criteria. To compare and improve the usability of WR devices, we, as a community, need to reach a consensus on what usability is, so we can choose the appropriate tools to assess it. We propose a set of 43 usability attributes identified in current WR practice and provide definitions validated by an international community. This work contributes to our efforts in creating a platform to support WR benchmarking, linked to the website: www.usabilitytoolbox.ch

Summary A civil engineering company co-designed a robotic exoskeleton with to decrease the employees exposition to high biomechanical constraints related to mechanical or automated tasks. The French Institute of Health and Safety (INRS) is following this company by for 4 years (2018-2022) aiming to understand and optimize the process of integration and employees’ acceptance of this specific device. This follow-up was carried out using the INRS tools, which are available to companies and occupational health specialists. This longitudinal follow-up highlighted the importance of scientific and technical education about this type of technology at different levels of the organization: individual, collective and organizational. Our communication will consist of presenting the results of the exoskeleton integration project follow-up.

Problem: “The human body changes shape throughout the day, and prosthetic fittings don’t.” Prosthetic limbs are attached to the residual leg with U-shaped solid structures called sockets. When the leg changes shape, sockets don’t fit anymore and break the skin, making amputees unable to walk for days. Solution: We developed the world’s first robotic liner; Roliner. Roliner is a sleeve-like device worn on the stump before putting the prosthetic limb on. It uses Artificial Intelligence to understand the hourly/daily changes in the stump and adapts to them. Reducing clinical dependency, Roliner’s AI reads real-time sensors’ data between the leg and socket, learns amputees’ comfort preferences via an app; seamlessly and continuously adjust the fitting by inflating/deflating Roliner’s micro-channels. (www.unhindr.com)

In the application-oriented R&D project ExoPflege, an assistive occupational exoskeleton with active shoulder-arm and adaptive trunk module is under development to support nursing staff members in hospitals. The primary goal is to support manual pushing and pulling motions during bed transfer of narcotized patients, an activity that was identified as physically demanding in a preliminary on-site analysis. A biomechanical model-based approach was used to analyze use-cases, as well as to select and optimize the exoskeleton design. The presentation will outline the application requirements, design process and the current status of the prototype development.

We propose a discussion on the extent to which currently available overground exoskeletons are versatile enough to accommodate specific demands across different clinical conditions leading to gait rehabilitation. We further address the lack of well-established rehabilitation protocols (e.g., dose and dosage), even when considering a single clinical population, and the limited availability of exoskeletons regulated for clinical use in Canada.

A the challenge on exoskeletons design is to maintain and conserve the anatomical and mechanical axis, more relevant when a mechanical joint or an actuator is implemented on an anatomical joint. At "Mobilab and Care" we have develop a digital workflow that using 3d scanners and markers allows for the correct implementation of this elements on exoskeletons.

To be accepted by the users on the shop floor, Exoskeletons need to satisfy their needs in terms of high usability and a positive user experience. Focusing on aspects like the users’ wearing comfort, reduction of interaction forces and easy setup, a new concept for a soft exoskeleton that supports the elbow movement during lifting tasks was developed.