Applied Bionics and Biomechanics

Snapping shrimp produces a high-speed jet through the rapid closure of the snapper claw, which stimulates the formation of cavitation bubbles of various shapes. In order to explore the fast motion characteristics of snapper claw, the formation and change process of cavitation, and the physical principles underlying the biological phenomena, the equivalent model of snapper claw was constructed through CT scanning technology. A high-speed camera was used to capture the claw’s motion characteristics, thereby simulating the production of cavitation bubbles by snapping shrimp. The results show that the rotation speeds of different species of snapping shrimps are different, as well as their motion characteristics. Cavitation is formed by the interaction of the pressure drop caused by the vortex at the nozzle with the inertia of the liquid inside the socket. Under the influence of the jet, the shapes of bubbles change from ring to cone, and eventually collapse into bubble clouds.

Background. Spinal cord injury (SCI) is a common severe trauma in clinic, hundreds of thousands of people suffer from which every year in the world. In terms of injury location, cervical spinal cord injury (CSCI) has the greatest impact. After cervical spinal cord injury, the lack of innervated muscles is not enough to provide ventilation and other activities to complete the respiratory function. In addition to the decline of respiratory capacity, respiratory complications also have a serious impact on the life of patients. The most commonly used assisted breathing and cough equipment is the ventilator, but in recent years, the functional electrical stimulation method is being used gradually and widely. Methods. About hundred related academic papers are cited for data analysis. They all have the following characteristics: (1) basic conditions of patients were reported, (2) patients had received nerve or muscle stimulation and the basic parameters, and (3) the results were evaluated based on some indicators. Results. The papers mentioned above are classified as four kinds of stimulation methods: muscle electric/magnetic stimulation, spinal dural electric stimulation, intraspinal microstimulation, and infrared light stimulation. This paper describes the stimulation principle and application experiment. Finally, this paper will compare the indexes and effects of typical stimulation methods, as well as the two auxiliary methods: training and operation. Conclusions. Although there is limited evidence for the treatment of respiratory failure by nerve or muscle stimulation after cervical spinal cord injury, the two techniques seem to be safe and effective. At the same time, light stimulation is gradually applied to clinical medicine with its strong advantages and becomes the development trend of nerve stimulation in the future.

The motion analysis of two-finger tip pinching using the thumb and index finger provides crucial data for designing the motion mechanism of electric prosthetic hands. The purpose of this study is to determine the joints that have high mobility during two-finger tip pinching by measuring the flexion angle of each joint. Ten Japanese men with normal hand were selected. CT images were obtained while the hands adopted the following four postures: a basic posture not pinching a cylinder, and three postures pinching wooden cylinders with different diameters (2, 10, and 30 mm). Three-dimensional bone models of the thumb and index finger were created using the CT images and used to measure the flexion angles of the joints. The flexion angles of the proximal interphalangeal and metacarpophalangeal joints of the index finger significantly decreased as the diameter of the cylinder increased. However, even when the diameter of the cylinder changed, the flexion angle of the distal interphalangeal joint of the index finger, and the flexion and rotation angles of all of the thumb joints did not change. When pinching objects of different sizes with a two-finger tip pinch, the posture of the thumb is fixed, and only the posture of the index finger changes. When designing the two-finger tip pinch motion for an electric prosthetic hand, it is sufficient to drive the joints of the index finger only.

In upper limb rehabilitation training by exploiting robotic devices, the qualitative or quantitative assessment of human active effort is conducive to altering the robot control parameters to offer the patients appropriate assistance, which is considered an effective rehabilitation strategy termed as assist-as-needed. Since active effort of a patient is changeable for the conscious or unconscious behavior, it is considered to be more feasible to determine the distributions of the passive resistance of the patient’s joints versus the joint angle in advance, which can be adopted to assess the active behavior of patients combined with the measurement of robotic sensors. However, the overintensive measurements can impose a burden on patients. Accordingly, a prediction method of shoulder joint passive torque based on a Backpropagation neural network (BPANN) was proposed in the present study to expand the passive torque distribution of the shoulder joint of a patient with less measurement data. The experiments recruiting three adult male subjects were conducted, and the results revealed that the BPANN exhibits high prediction accurate for each direction shoulder passive torque. The results revealed that the BPANN can learn the nonlinear relationship between the passive torque and the position of the shoulder joint and can make an accurate prediction without the need to build a force distribution function in advance, making it possible to draw up an assist-as-needed strategy with high accuracy while reducing the measurement burden of patients and physiotherapists.

Sit-to-stand (STS) motion is an indicator of an individual’s physical independence and well-being. Determination of various variables that contribute to the execution and control of STS motion is an active area of research. In this study, we evaluate the clinical hypothesis that besides numerous other factors, the central nervous system (CNS) controls STS motion by tracking a prelearned head position trajectory. Motivated by the evidence for a task-oriented encoding of motion by the CNS, we adopt a robotic approach for the synthesis of STS motion and propose this scheme as a solution to this hypothesis. We propose an analytical biomechanical human CNS modeling framework where the head position trajectory defines the high-level task control variable. The motion control is divided into low-level task generation and motor execution phases. We model CNS as STS controller and its Estimator subsystem plans joint trajectories to perform the low-level task. The motor execution is done through the Cartesian controller subsystem that generates torque commands to the joints. We do extensive motion and force capture experiments on human subjects to validate our analytical modeling scheme. We first scale our biomechanical model to match the anthropometry of the subjects. We do dynamic motion reconstruction through the control of simulated custom human CNS models to follow the captured head position trajectories in real time. We perform kinematic and kinetic analyses and comparison of experimental and simulated motions. For head position trajectories, root mean square (RMS) errors are 0.0118 m in horizontal and 0.0315 m in vertical directions. Errors in angle estimates are 0.55 rad, 0.93 rad, 0.59 rad, and 0.0442 rad for ankle, knee, hip, and head orientation, respectively. RMS error of ground reaction force (GRF) is 50.26 N, and the correlation between ground reaction torque and the support moment is 0.72. Low errors in our results validate (1) the reliability of motion/force capture methods and anthropometric technique for customization of human models and (2) high-level task control framework and human CNS modeling as a solution to the hypothesis. Accurate modeling and detailed understanding of human motion can have significant scope in the fields of rehabilitation, humanoid robotics, and virtual characters’ motion planning based on high-level task control schemes.

This paper establishes design criteria for soft exogloves (SEG) to be used as rehabilitation or assistance devices. This research consists in identifying, selecting, and grouping SEG features based on the analysis of 91 systems that have been proposed during the last decade. Thus, function, mobility, and usability criteria are defined and explicitly discussed to highlight SEG design guidelines. Additionally, this study provides a detailed description of each system that was analysed including application, functional task, palm design, actuation type, assistance mode, degrees of freedom (DOF), target fingers, motions, material, weight, force, pressure (only for fluids), control strategy, and assessment. Such characteristics have been reported according to specific design methodologies and operating principles. Technological trends are contemplated in this contribution with emphasis on SEG design opportunity areas. In this review, suggestions, limitations, and implications are also discussed in order to enhance future SEG developments aimed at stroke survivors or people with hand disabilities.