Analysis and Clustering of Upper Limb Motion during the Hand Dexterity Pegboard Test using Inertial Sensor Systems.

Maintaining hand and upper limb mobility is important from the viewpoint of freedom in daily life and high performance in work. Few studies on the mobility and dexterity of the upper limb have focused on detailed hand and finger movements. Therefore, we measured the motion of the upper limbs during a general hand dexterity pegboard test using inertial sensor systems and our previous measuring method. To clarify the characteristics of each purpose of motion, we divided the peg-in-hole motion in the pegboard test into its three sections, focusing on two sections: the pinch section, and the carry and insert section. In addition, the obtained joint angles were grouped into arm group and finger group, and singular value decomposition was performed for each joint group in each section. By clustering the decomposition results across five subjects' multiple right and left arm tests, and averaging the singular vectors in the same cluster, the joint distributions and combinations could be clarified. In addition, by recalculating joint angles from averaged SVD results and applying them to the rigid link model, we obtained motion animation with characteristics that made it possible to more clearly understand the requirements for greater dexterity. These results suggested high dexterity motion characteristics in the pinch section, and the carry and insert section of the pegboard test.

Analysis of Dexterity Motion by Singular Value Decomposition for Hand Movement Measured Using Inertial Sensors.

Finger movements play an important role in many daily human actions. Among the studies on the dexterity of fingers required for various tasks in neurology and simple evaluation tests, few have focused on detailed finger movements themselves. Therefore, in this study, we improved the hand motion measurement system using inertial sensors and the motion analysis method developed in our previous study and measured the motion of the upper limbs (including the fingers) during a general finger dexterity test. By applying singular value decomposition to the obtained joint angles and decomposing them into simpler movement units, we obtained the timing of each movement unit and the purpose of each movement as the coordination state of the joints. By applying hierarchical clustering to multiple trials in a finger dexterity test, we also determined the similarity between trials and investigated the characteristics of movements with higher dexterity. We investigated the motor characteristics in finger dexterity by analyzing our results.

Exposure-response analysis of drug-induced QT interval prolongation in telemetered monkeys for translational prediction to human.

INTRODUCTION: The preclinical in vivo assay for QT prolongation is critical for predicting torsadogenic risk, but still difficult to extrapolate to humans. This study ran preclinical tests in cynomolgus monkeys on seven QT reference drugs containing the drugs used in the IQ-CSRC clinical trial and applied exposure-response (ER) analysis to the data to investigate the potential for translational information on the QT effect. METHODS: In each of six participating facilities in the J-ICET project, telemetered monkeys were monitored for 24 h following administration of vehicle or 3 doses of test drugs, and pharmacokinetic profiles at the same doses were evaluated separately. An individual rate-corrected QT interval (QTca) was derived and the vehicle-adjusted change in QTca from baseline (∆∆QTca) was calculated. Then the relationship of concentration to QT effect was evaluated by ER analysis. RESULTS: For QT-positive drugs in the IQ-CSRC study (dofetilide, dolasetron, moxifloxacin, ondansetron, and quinine) and levofloxacin, the slope of the total concentration-QTca effect was significantly positive, and the QT-prolonging effect, taken as the upper bound of the confidence interval for predicted ∆∆QTca, was confirmed to exceed 10 ms. The ER slope of the negative drug levocetirizine was not significantly positive and the QTca effect was below 10 ms at observed peak exposure. DISCUSSION: Preclinical QT assessment in cynomolgus monkeys combined with ER analysis could identify the small QT effect induced by several QT drugs consistently with the outcomes in humans. Thus, the ER method should be regarded as useful for translational prediction of QT effects in humans.

Hand Motion Measurement using Inertial Sensor System and Accurate Improvement by Extended Kalman Filter.

Analysis of hand motions is crucial in such actual conditions as daily life and traditional work. We developed a measurement system using inertial sensors instead of an optical motion capture system that measures with spatial constraints. However, for these sensors, the posture error caused by the integration of the angular velocity is critical. A typical solution uses sensor fusion with simple observation equations to measure such lower limbs by walking analysis. For finger motions, a simple observation, calculated identically as the initial posture, is unsuitable because fingers may be moved intricately and quickly by multiple joints and parallel links. Therefore, we constructed an observation equation based on such dynamic acceleration as rotational acceleration and the correction of compass error. Using this suggested observation equation, since both the posture and position error were verified in the hand and forearm motions by a comparison with the optical motion capture, we could measure them with high accuracy. After measuring the movements of an actual hand, such as writing words and spinning a top, we analyzed the characteristics from a reproduced link model and joint angles.

Modeling of Hand and Forearm Link using Inertial Sensors.

In this paper, we describe our hand and forearm motion measuring system using inertial sensors. Although a sensor axis is often used to measure human body motion, it is prone to attachment and offset error, and, because a hand is made of five parallel links, it is not suitable for hand measurement. Therefore, we propose a method of modeling the hand and forearm link using only sensors. To model a finger link, a compass' azimuth deviation is important because it may affect the intersection of the fingers. Therefore, before modeling, we applied correction and alternative methods using the angular velocity direction. As a result, the deviation between the sensors decreased to 1/5. During the modeling, we estimated the sensor's position vectors on the distal and next distal segments from each joint, and calculated the relationship matrices between the sensors through initial posture during estimation. We created the hand and forearm link model by combining the position vectors and relationship matrices. Comparison with optical motion capture showed that the hand shape without intersection of the fingers matched well, but there was offset because the forearm sensors deviated from the estimated positions. Although we must improve the attachment to the forearm, these methods proved effective for hand motion measurement.

Estimation of joint center and measurement of finger motion by inertial sensors.

The authors developed a wearable finger motion measurement system using inertial and geomagnetic sensors. Using this system, motion and posture of the hands and fingers can be measured. However, the joint center and segment axis cannot be accurately measured in a previous study using the sensors. Therefore, the authors proposed a method of estimating the joint center and segment lengths. This method utilizes the fact that the calculation formula of the rotational acceleration in the sensor's coordinate system is the vector product. However, because the vector product is irreversible, the rotation center was calculated by using a position vector placed on an intersection line of two planes constituted by rotational acceleration. As a result of the verification, estimation error was small. In addition, finger motion was measured using posture measurement and rotation center estimation. This measured motion, joint angle and segment lengths estimated by the finger motion measurement system were compared with a motion capture system. As a result, the initial MP and PIP joint angles had some differences, but there was no difference for the MP and PIP joint angles during movement and the other joint angles. Therefore, we need to improve the estimation method of the PIP and DIP joint centers.

Involvement of the Tyro3 receptor and its intracellular partner Fyn signaling in Schwann cell myelination.

During early development of the peripheral nervous system, Schwann cell precursors proliferate, migrate, and differentiate into premyelinating Schwann cells. After birth, Schwann cells envelop neuronal axons with myelin sheaths. Although some molecular mechanisms underlying myelination by Schwann cells have been identified, the whole picture remains unclear. Here we show that signaling through Tyro3 receptor tyrosine kinase and its binding partner, Fyn nonreceptor cytoplasmic tyrosine kinase, is involved in myelination by Schwann cells. Impaired formation of myelin segments is observed in Schwann cell neuronal cultures established from Tyro3-knockout mouse dorsal root ganglia (DRG). Indeed, Tyro3-knockout mice exhibit reduced myelin thickness. By affinity chromatography, Fyn was identified as the binding partner of the Tyro3 intracellular domain, and activity of Fyn is down-regulated in Tyro3-knockout mice, suggesting that Tyro3, acting through Fyn, regulates myelination. Ablating Fyn in mice results in reduced myelin thickness. Decreased myelin formation is observed in cultures established from Fyn-knockout mouse DRG. Furthermore, decreased kinase activity levels and altered expression of myelination-associated transcription factors are observed in these knockout mice. These results suggest the involvement of Tyro3 receptor and its binding partner Fyn in Schwann cell myelination. This constitutes a newly recognized receptor-linked signaling mechanism that can control Schwann cell myelination.

Measurement of rehabilitation in thumb MP joint subluxation due to rheumatoid arthritis.

As treatment for subluxation due to rheumatoid arthritis (RA), rehabilitation by hand therapy is one option, but the number of therapist is not sufficient. Therefore, a device for rehabilitation of thumb metacarpophalangeal (MP) joint subluxation has been developed. To improve the device, it is necessary to measure in close proximity to the actual rehabilitation. Therefore, the authors tried to measure two kinds of rehabilitation by using motion capture and a contact force sensor. To measure rehabilitation movements, three markers were attached to the metacarpal bone, six markers were attached to each side of the interphalangeal (IP) joint, MP joint and proximal phalanx of the right thumb of the subjects, and a finger model was created by these markers. Further, three markers were placed on the left index of the therapist, and force direction was calculated by these markers. Measurement was conducted on healthy subjects, Rehabilitation was performed by the person who is not a therapist, but received the guidance of the doctor who is coauthor. As a result, the authors could measure rehabilitation by hand therapy, force, point of action and displacement. The results suggest that rehabilitation with traction twice as efficient as that without traction. Furthermore, it was found that rehabilitation is possible with calculated force, and the force is reproducible by the actuator in the device.

Motion discrimination technique by EMG signals using hyper-sphere model.

This study developed a method of discriminating real-time motion from electromyogram (EMG) signals. We previously proposed a real-time motion discrimination method using hyper-sphere models that discriminated five motions (open, grasp, pinching, wrist extension, and wrist flexion) above 90% and quickly learned EMG signals. Our method prevents elbow motions from interfering with hand motion discrimination. However, we presume in our method that feature quantities do not change with time. Discrimination accuracy might deteriorate over time. Additionally, our method only discriminated three motions (open, grasp, pinching) for finger motions. This paper proposes the effectiveness of our method for changing feature quantities caused by time variation and a real-time motion discrimination method using new hyper-sphere models for four finger motions (open, grasp, pinching, and 2-5th finger flexion). We carried out two experiments and verified the effectiveness of our method for changing feature quantities and four finger motions discrimination using the new hyper-sphere models.

Quantitative evaluation of unrestrained human gait on change in walking velocity.

In human gait motion analysis, which is one useful method for efficient physical rehabilitation to define various quantitative evaluation indices, ground reaction force, joint angle and joint loads are measured during gait. To obtain these data as unrestrained gait measurement, a novel gait motion analysis system using mobile force plates and attitude sensors has been developed. On the other hand, a human maintains a high correlation among the motion of all joints during gait. The analysis of the correlation in the recorded joint motion extracts a few simultaneously activating segmental coordination patterns, and the structure of the intersegmental coordination is attracting attention to an expected relationship with a control strategy. However, when the evaluation method using singular value decomposition has been applied to joint angles of the lower limb as representative kinematic parameters, joint moments related to the rotational motion of the joints have not yet been considered. In this paper, joint moments as kinetic parameters applied on the lower limb during gait of a normal subject and a trans-femoral amputee are analyzed under change in walking velocity by the wearable gait motion analysis system, and the effectiveness for quantitatively evaluate the rotational motion pattern in the joints of the lower limb by using joint moments is validated.

Autologous mesenchymal stem cell-derived dopaminergic neurons function in parkinsonian macaques.

A cell-based therapy for the replacement of dopaminergic neurons has been a long-term goal in Parkinson's disease research. Here, we show that autologous engraftment of A9 dopaminergic neuron-like cells induced from mesenchymal stem cells (MSCs) leads to long-term survival of the cells and restoration of motor function in hemiparkinsonian macaques. Differentiated MSCs expressed markers of A9 dopaminergic neurons and released dopamine after depolarization in vitro. The differentiated autologous cells were engrafted in the affected portion of the striatum. Animals that received transplants showed modest and gradual improvements in motor behaviors. Positron emission tomography (PET) using [11C]-CFT, a ligand for the dopamine transporter (DAT), revealed a dramatic increase in DAT expression, with a subsequent exponential decline over a period of 7 months. Kinetic analysis of the PET findings revealed that DAT expression remained above baseline levels for over 7 months. Immunohistochemical evaluations at 9 months consistently demonstrated the existence of cells positive for DAT and other A9 dopaminergic neuron markers in the engrafted striatum. These data suggest that transplantation of differentiated autologous MSCs may represent a safe and effective cell therapy for Parkinson's disease.