An exoskeleton configured to be coupled to a person includes an exoskeleton trunk and leg supports adapted to contact the ground. Hip torque generators extend between the exoskeleton trunk and respective leg supports. A load holding mechanism is rotatably coupled to the exoskeleton trunk, preferably via over-shoulder members configured to support a load in front of the person. In use, hip torque generators create torque between the exoskeleton trunk and respective leg supports in the stance phase, wherein at least one torque generator is configured to create a first torque between the exoskeleton trunk and one of the first and second leg supports in the stance phase opposing a second torque generated on the exoskeleton by a weight of the load. Load bearing sensors may be utilized to determine the torque generated by the load and communicate with a controller to control power to the torque generators.

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In this paper a human upper limb robotic system is analyzed through an experimental study. The experimental analysis aim is to validate this robotic system type in order to use it in some kinetotherapy programs for the human upper limb recovery. The robotic system experimental research was performed by using equipment called SIMI Motion which enables to evaluate angular variations in 2D environment. Through this equipment used we establish the angular variations developed at the robotic system joints level. This paper consists of three main parts. In the first part there is an actual study of the robotic systems specially designed for the human upper limb rehabilitation, and in second part, the robotic system proposed for this experimental research is described. In the third part the experimental research is described in detail.

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A 28-year-old woman, with incomplete spinal cord injury at the C2 level, classified as American Spinal Injury Impairment Scale C (AIS), participated in a robotic rehabilitation program 29 months after injury. Robotic training was provided to both upper extremi-ties using the MAHI Exo-II, an exoskeleton device designed for rehabilitation of the upper limb, for 12 × 3-h sessions over 4 weeks. Training involved elbow flexion/extension, forearm supination/pronation, wrist flexion/extension, and radial/ulnar deviation.
Results: Outcome measures were Action Research Arm Test, Jebsen-Taylor Hand Function Test, and AIS-upper extremity motor score. Sa-fety measures included fatigue, pain and discomfort level using a 5-point rating scale. Following training, improvements were ob-served in the left arm and hand function, whereas the right arm and hand function showed no improvement in any of the functional outcome measures. No excessive pain, discomfort or fatigue was reported. Conclusion: Data from one subject demonstrate valuable information on the feasibility, safety and effectiveness of robotic-assisted training of upper-extremity motor functions after in-complete spinal cord injury.

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A portable load lifting assist system (100) includes a movable support structure including an exoskeleton torso (160) including an exoskeleton trunk (109) that is configured to be coupled to a person’s upper body, and a load lifting mechanism (221) secured to the movable support structure including a winch (229) having a motor driven reel mechanism for reeling first and second lifting straps or cables (222) that are secured to first and second end effectors (223). First and second handles (224) are attached to an outside surface of the first and second end effectors, wherein the lifting straps or cables when driven by the winch lift a load contacted by the first and second end effectors. A lower extremity exoskeleton (120) is configured to be coupled to a person’s lower limbs. The exoskeleton trunk couples to the person’s upper body through an upper body interface device (150) that is coupled to the lower extremity exoskeleton.

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Provided is a walking motion assisting device capable of assisting a leg of an agent in walking motion to alleviate an assisting burden or eliminate an assisting necessity by a caregiver. According to the walking motion assisting device (1), the value of a persistent energy input term (ζ0) contained in a simultaneous differential equation denoting a second model configured to generate a second motion oscillator (φ1) is adjusted so as to limit a landing position (x) of a leg of the agent in a specified range [x1, x2]. Further, the motion state of the leg is recognized on the basis of a variation mode of a second oscillator (ξ2), and on the basis of the recognition result, the relative motion between the thigh and crus of the leg around the knee joint is assisted.

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