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Knowledge of the changes in the behavior of human soft tissue stiffness during physical impact in human–machine interaction (HMI) plays a vital role in the development of biofidelity testing devices such as a human dummy. These testing devices are widely applied as an effective means to validate the safety of machinery during dynamic or static contact with humans in HMI. In this study, we assess changes in soft tissue stiffness in the upper arm of individuals under both dynamic (0.7 and 0.25 m/s) and quasi‐static (QS) impacts under a constrained contact condition. Three impactor shapes (cylindrical, cubic, and spherical) are used in this study. Impact experiments are conducted using impactors attached to a pendulum. The soft‐tissue displacement is determined using an ultrasound device. The impact force‐displacement curves illustrate the nonlinear behavior of the soft tissue stiffness under both dynamic and QS impacts. By utilizing the "Linear Mixed Model" statistical analysis, we found that changes in the impact velocity significantly influenced the changes in the nonlinear behavior of soft tissue stiffness while there was no significant effect of the changes in the impactor shape on the nonlinear behavior of the soft tissue stiffness. Additionally, we revealed that the changes in the soft tissue stiffness are influenced by the size of the contact area. Moreover, we demonstrated a range of changes in soft tissue stiffness for different impact velocities, which provide valuable information for developing future validation test devices in HMI, such as the design and evaluation of dummy skin. [ABSTRACT FROM AUTHOR]

This study presents a novel concept of robust Kalman filtering, especially dealing with outliers when detecting human hand intrusion using multiple-input–multiple-output radar. Outliers that severely deviate from the normal value for a certain period have not been sufficiently discussed from the viewpoint of safety and can seriously hamper the performance of the Kalman filter. Therefore, two types of outliers were intensively discussed: the temporary outlier that originated in misdetection and the additive outlier that is generated by heavy-tailed error distribution noise. Moreover, an asymmetric outlier processing strategy was proposed depending on positive and negative outliers. The result shows that the proposed method can resist the additive and temporary outliers. [ABSTRACT FROM AUTHOR]

Interaction forces between a robotic cuff and the skin during assisted walking with a lower limb exoskeleton may cause skin injuries over time, such as blisters and ulcers. This study proposes a sensing cuff that can monitor the contact behavior between the exoskeleton and skin during assisted walking, and a functional test and assisted walking experiments were conducted to evaluate the performance of the proposed device. The functional test of the sensing cuff showed good performance of capturing the contact behavior for safety evaluation. The walking experiment involved subjects walking on a treadmill with a lower limb exoskeleton under different conditions (i.e., walking speed and clothing), and the sensing cuff attached to the exoskeleton measured the interaction forces and slip velocity. The magnitude of shear force in the movement direction peaked near the beginning and within 40 – 50% of the gait cycle. The contact safety of the lower limb exoskeleton during assisted walking was then evaluated based on the calculated shear stress. The designed sensing cuff could provide sufficient information regarding contact behavior and contact safety during assisted walking. [ABSTRACT FROM AUTHOR]

Stretching is a major treatment for restoring the ankle range of motion while decreasing the ankle stiffness. An automatic stretching machine can provide long-term continual stretching at home. However, no commercial stretching machines are currently available, and therefore, no safety guidelines exist for them. In this study, we prototyped a stretching machine using a chassis from a commercial foot exerciser for preventing disuse syndrome, and then proposed three safety concepts as general requirements for stretching machines. The concepts were determined based on risk assessments, which included (1) preventing excessive force from being applied to the foot, (2) responding to the ankle stiffness and the range of motion of each different individual, and (3) preventing unintended operations by the user. The above concepts allowed us to develop a stretching machine taking into account safety measures. Further, the stretching effect of the prototype was tested on sixteen healthy young subjects ( 22.3 ± 3.6 years ). We found that the passive resistance of the subjects at specific dorsiflexion angles decreased significantly after stretching the ankle using the prototyped machine. [ABSTRACT FROM AUTHOR]

Continuous use of wearable robots can cause skin injuries beneath the cuffs of robots. To prevent such injuries, understanding the contact behavior of the cuff is important. Thus far, this contact behavior has not been studied because of the difficulty involved in measuring the slippage under the cuff. In this study, for the first time, the relative displacement, slippage, and interaction force and moment at the thigh cuff of a robot during sit-to-stand motion were measured using an instrumented cuff, which was developed for this purpose. The results indicated that the slippage and relative displacement under the cuff was uneven because of the rotation of the cuff, which suggests that the risk of skin injuries is different at different positions. Especially, the skin closer to the hip showed larger dynamism, with a maximum slippage of approximately 10 mm and a displacement of 20 mm during motion. Another important phenomenon was the individual difference among subjects. During motion, the interaction force, moment, and slippage of some subjects suddenly increased. Such behavior results in stress concentration, which increases the risk of skin injuries. These analyses are intended to understand how skin injuries are caused and to design measures to prevent such injuries. [ABSTRACT FROM PUBLISHER]

Most lower-limb physical assistant robots are fixed to wearers using cuffs. Hence, skin injuries beneath the cuffs are one of the major concerns of the users. A model that describes the relationship between the body posture and the interaction forces at the cuff was developed for use in assessing the risk of injury and improving user comfort. We measured the motion and interaction force beneath cuffs during the sitting and standing motions of subjects and a physical assistant robot which has been hardly reported thus far. Because of slippage and biomechanical motion, a traditional spring-damper model was found to be insufficient to describe the interaction forces associated with the measured motion of the cuffs. A parameter representing the motion or the knee joint angle was added to take into account these factors. Our model for estimation of the interaction forces using a spring, a damper, and the attitude of the lower leg fits the measured data especially well for the thigh cuff and is better than the traditional model. The applicability of this model was verified for several assist modes and wearers. The model was found to describe approximately 90% of the burden on the wearer, which reached a peak of approximately 60 N, the most hazardous condition. Having been validated for a commercial assistant robot, the model can be used to estimate the skin burdens beneath the cuffs without any force-sensitive elements. [ABSTRACT FROM AUTHOR]

Human-cooperative robots (HCRs) are expected to benefit various fields. Safety functions are essential to the control system of HCRs because their hazardous movements after a system failure may cause serious injuries to operators. Therefore, their reliability must be sufficiently high relative to the estimated risk, and it is important to design a suitable safety function for the control system to match the safety level required for an HCR. We propose a methodology of safety-function design for the control system of an HCR and attempt to effectively combine design approaches for hardware and software of safety-related systems (SRSs) on the basis of the concept of functional safety. This study describes the details of the methodology for an HCR that we adopted as a platform system. First, SRS hardware with a dual-channel voting architecture was designed, and then, functional safety analysis was performed to verify whether the hardware satisfied the required safety integrity level (SIL). Next, SRS software with diverse programming, which is recommended for the required SIL, was designed by utilizing a disturbance observer. Finally, experiments were conducted on the SRS for representative failures and the safety function was verified for the control system, as set by the proposed methodology. [ABSTRACT FROM PUBLISHER]

The objective of our study is to develop a safety measure that ensures smooth control mode switching of an intelligent assist device (IAD)—Skill-Assist for the purpose of effective automotive manufacturing. Smooth switching, i.e., switching without abrupt deceleration, from the hands-off control mode (used for automatic travel) to the hands-on control mode (as typified by a power-assist control mode) is expected to enhance the productivity of IADs. However, the hazardous behaviors, i.e., careless behaviors that disregard an approaching IAD in hands-off control mode might cause collision and serious injuries to a human operator. For safety purposes, we focused on the operator's gesture of reaching for the force sensor of the Skill-Assist. Laser range sensors were employed to recognize the reaching gesture during control mode switching. A reaching gesture recognition algorithm, based on a hidden Markov model, processes characteristic patterns acquired by the laser range sensors, and judges the operator safety. Experimental results suggest that the Skill-Assist to which the proposed safety measure was applied could recognize the reaching gesture of an operator when the control mode was smoothly switched. In an experiment on hazardous behavior, the Skill-Assist could predict that the operator would be unsafe. [ABSTRACT FROM PUBLISHER]