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Back support exoskeletons are designed to prevent work-related low-back pain by reducing mechanical loading. For actuated exoskeletons, support based on moments actively produced by the trunk muscles appears a viable approach. The moment can be estimated by a biomechanical model. However, one of the main challenges here is the feasibility of recording the required input variables (kinematics, EMG data, ground reaction forces) to run the model. The aim of this study was to evaluate how accurate different selections of input variables can estimate actively generated moments around L5/S1. Different multivariate regression analyses were performed using a dataset consisting of spinal load, body kinematics and trunk muscle activation levels during different lifting conditions with and without an exoskeleton. The accuracy of the resulting models depended on the number and type of input variables and the regression model order. The current study suggests that third-order polynomial regression of EMG signals of one or two bilateral back muscle pairs together with exoskeleton trunk and hip angle suffices to accurately estimate the actively generated muscle moment around L5/S1, and thereby design a proper control system for back support exoskeletons. © 2020 Elsevier Ltd

Back support exoskeletons are designed to prevent work-related low-back pain by reducing mechanical loading. For actuated exoskeletons, support based on moments actively produced by the trunk muscles appears a viable approach. The moment can be estimated by a biomechanical model. However, one of the main challenges here is the feasibility of recording the required input variables (kinematics, EMG data, ground reaction forces) to run the model. The aim of this study was to evaluate how accurate different selections of input variables can estimate actively generated moments around L5/S1. Different multivariate regression analyses were performed using a dataset consisting of spinal load, body kinematics and trunk muscle activation levels during different lifting conditions with and without an exoskeleton. The accuracy of the resulting models depended on the number and type of input variables and the regression model order. The current study suggests that third-order polynomial regression of EMG signals of one or two bilateral back muscle pairs together with exoskeleton trunk and hip angle suffices to accurately estimate the actively generated muscle moment around L5/S1, and thereby design a proper control system for back support exoskeletons. © 2020 Elsevier Ltd

With mechanical loading as the main risk factor for LBP, exoskeletons (EXO)are designed to reduce the load on the back by taking over part of the moment normally generated by back muscles. The present study investigated the effect of an active exoskeleton, controlled using three different control modes (INCLINATION, EMG & HYBRID), on spinal compression forces during lifting with various techniques. Ten healthy male subjects lifted a 15 kg box, with three lifting techniques (free, squat & stoop), each of which was performed four times, once without EXO and once each with the three different control modes. Using inverse dynamics, we calculated L5/S1 joint moments. Subsequently, we estimated spine forces using an EMG-assisted trunk model. Peak compression forces substantially decreased by 17.8% when wearing the EXO compared to NO EXO. However, this reduction was partly, by about one third, attributable to a reduction of 25% in peak lifting speed when wearing the EXO. While subtle differences in back load patterns were seen between the three control modes, no differences in peak compression forces were found. In part, this may be related to limitations in the torque generating capacity of the EXO. Therefore, with the current limitations of the motors it was impossible to determine which of the control modes was best. Despite these limitations, the EXO still reduced both peak and cumulative compression forces by about 18%. © 2019 Elsevier Ltd

With mechanical loading as the main risk factor for LBP, exoskeletons (EXO)are designed to reduce the load on the back by taking over part of the moment normally generated by back muscles. The present study investigated the effect of an active exoskeleton, controlled using three different control modes (INCLINATION, EMG & HYBRID), on spinal compression forces during lifting with various techniques. Ten healthy male subjects lifted a 15 kg box, with three lifting techniques (free, squat & stoop), each of which was performed four times, once without EXO and once each with the three different control modes. Using inverse dynamics, we calculated L5/S1 joint moments. Subsequently, we estimated spine forces using an EMG-assisted trunk model. Peak compression forces substantially decreased by 17.8% when wearing the EXO compared to NO EXO. However, this reduction was partly, by about one third, attributable to a reduction of 25% in peak lifting speed when wearing the EXO. While subtle differences in back load patterns were seen between the three control modes, no differences in peak compression forces were found. In part, this may be related to limitations in the torque generating capacity of the EXO. Therefore, with the current limitations of the motors it was impossible to determine which of the control modes was best. Despite these limitations, the EXO still reduced both peak and cumulative compression forces by about 18%. © 2019 Elsevier Ltd

The load that is carried in military backpacks has drastically increased over the years. Besides energy expenditure, load carriage increases joint loading which has been associated with an increased risk on injuries, discomfort, and reduced task performance. To support soldiers during load carrying, exoskeletons have been proposed. The use of exoskeletons for load carrying is limited since current active exoskeletons have the disadvantage that their power requirements make them unsuitable for long use and (quasi-)passive exoskeletons have mainly focused on metabolic cost. In this paper we present the Exobuddy exoskeleton. The Exobuddy transfers a part of the load directly to the ground. The Exobuddy mechanism is quasi-passive and thereby eliminates the need for large energy sources associated with active exoskeletons. The Exobuddy was evaluated in indoor and outdoor conditions, each completed by four subjects. Exobuddy unloaded the subjects by transferring on average approximately 30% (130 N) of the load to the ground with a maximum of 53% right after heel strike. The energy drawn from the human body to power the quasi-passive mechanism led only to a small, non-significant, increase in energy expenditure. Although not significant, carrying loads with Exobuddy was perceived less exerted and more comfortable compared to carrying loads with the current backpack. © 2018 IEEE.

This paper presents the structure and the main innovations of P.I.G.R.O. (Pneumatic Interactive Gait Rehabilitation Orthosis). It is an active exoskeleton electro-pneumatically controlled with 6 DoF (Degree of Freedom) in the sagittal plane. Robotic neurorehabilitation trainings are its main field of application. Some preliminary tests are carrying on with brain stroke and ictus patients.

Two mechatronics prototypes, useful for robotic neurotreatments and new clinical trainings, are here presented. P.I.G.R.O. (pneumatic interactive gait rehabilitation orthosis) is an active exoskeleton with an electropneumatic control. It imposes movements on lower limbs in order to produce in the patient’s brain proper motor cortex activation. Bra.Di.P.O. (brain discovery pneumatic orthosis) is an MR-compatible device, designed to improve fMRI (functional magnetic resonance imaging) analysis. The two devices are presented together because both are involved in the study of new robotic treatments of patients affected by ictus or brain stroke or in some motor learning experimental investigations carried out on healthy subjects.

По данным отечественной и зарубежной литературы проанализировано состояние проблемы разработки и внедрения экзоскелетов. Показано, что в настоящее время приоритетными областями применения экзоскелетов являются военная промышленность и реабилитационная медицина. Отмечено, что большинство созданных экзоскелетов не могут найти массового применения в реабилитации больных с ограничением функций верхних и нижних конечностей из-за большой массы конструкции, зависимости от источников внешнего питания, значительной стоимости. Рассмотрены особенности двух видов экзоскелетов: активного и пассивного. Показано, что наиболее приемлема для использования конструкция пассивного экзоскелета. Отмечено, что основные группы нуждающихся в экзоскелетах состоят из пациентов, страдающих парезами верхних и нижних конечностей., The problem of development and implementation of exoskeletons has been analyzed on the basis of the Russian and foreign literature. Military industry and rehabilitation medicine are shown to be currently the priority fields of exoskeleton application. It has been noted, that the majority of the existing exoskeletons cannot be widely used for the rehabilitation of the patients with limited functions of the upper and lower limbs because they are heavy, external power supply-dependent, and expensive. Two types of exoskeletons, active and passive, have been considered. The design of the passive exoskeleton is shown to be most acceptable for use. The analysis has revealed, that the main groups requiring exoskeletons, include patients suffering from paresis of the upper and lower limbs.

Motor rehabilitation techniques based on passive movement of the lower limbs have been developed over the past 15 years. Gait training automation is the latest innovation in these techniques. This paper describes the design and development of a pneumatic interactive gait rehabilitation orthosis (PIGRO), as well as the first experimental results obtained with healthy subjects. PIGRO consists of a modular and size-adaptable exoskeleton, pneumatic actuation systems for the six actuated degrees of freedom (DoF), and a control unit. The foot orthosis and ankle actuation can be removed and/or replaced with orthopaedic shoes so as to permit gait rehabilitation while advancing between parallel bars with ground contact and partial body weight support (i.e. not walking in place). Control logic provides closed-loop position control independently on each joint, with position feedback for each joint in real time. Imposed curves are physiological joint angles: it is also possible to choose between activating one or both legs and to modify curves to obtain different gait patterns if required. The paper concludes with a presentation of experimental results for the device's performance.