Development of Neonatal Airway Management Simulator for Evaluation of Tracheal Intubation

The long-term goal of this study is a training system that can simulate medical cases and advise physicians based on quantitative evaluation of neonatal resuscitation. In this paper, we designed and manufactured a neonatal airway management simulator for quantitative evaluation of tracheal intubation. This robotic simulator is equipped with 25 sensors of 6 types, which detect motions that lead to complications, inside the manikin replicated a neonate. A performance experiment of the developed sensor and an evaluation experiment with physicians were conducted. We observed that an erroneous operation in the laryngoscopy can be detected by the sensors in our simulator.

Construction of Automatic Scoring System to Support Objective Evaluation of Clinical Skills in Medical Education

In this study, we focused on the automatic scoring of medical clinical abilities. The objective clinical ability tests that all undergraduate students take before starting clinical practice were considered. As these tests evaluate practical skills, there is a problem that the learning method is poor compared to the examination of other lectures. Therefore, in this study, we recorded the voice of a student examining a simulated patient using a microphone. We constructed a system comprising a speech recognition module and a scoring system that performed automatic scoring by checking against a prepared example answer. This system was evaluated by medical doctors.

Placing and scheduling many depth sensors for wide coverage and efficient mapping in versatile legged robots

This article tackles the problem of designing 3D perception systems for robots with high visual requirements, such as versatile legged robots capable of different locomotion styles. In order to guarantee high visual coverage in varied conditions (e.g., biped walking, quadruped walking, ladder climbing), such robots need to be equipped with a large number of sensors, while at the same time managing the computational requirements that arise from such a system. We tackle this problem at both levels: sensor placement (how many sensors to install on the robot and where) and run-time acquisition scheduling under computational constraints (not all sensors can be acquired and processed at the same time). Our first contribution is a methodology for designing perception systems with a large number of depth sensors scattered throughout the links of a robot, using multi-objective optimization for optimal trade-offs between visual coverage and the number of sensors. We estimate the Pareto front of these objectives through evolutionary optimization, and implement a solution on a real legged robot. Our formulation includes constraints on task-specific coverage and design symmetry, which lead to reliable coverage and fast convergence of the optimization problem. Our second contribution is an algorithm for lowering the computational burden of mapping with such a high number of sensors, formulated as an information-maximization problem with several sampling techniques for speed. Our final system uses 20 depth sensors scattered throughout the robot, which can either be acquired simultaneously or optimally scheduled for low CPU usage while maximizing mapping quality. We show that, when compared with state-of-the-art robotic platforms, our system has higher coverage across a higher number of tasks, thus being suitable for challenging environments and versatile robots. We also demonstrate that our scheduling algorithm allows higher mapping performance to be obtained than with naïve and state-of-the-art methods by leveraging on measures of information gain and self-occlusion at low computational costs.

Knee extensor muscular activity estimation during different walking patterns: flat normal and brisk walking, stair climbing

Preserving mobility, the ability to keep a correct posture and dynamic balance in order to walk properly, is fundamental to maintain autonomy in daily life. Based on the correlation between muscle groups and autonomy, previous research has suggested that maintaining muscular tone in knee extensors is critical. Continuous training of knee extensors during aging is therefore essential to maintain independence. In this work, it is hypothesized that it is possible to estimate knee extensor activity only from IMU data based on a simple lower limbs model. The accuracy of the knee extensor activity estimation algorithm has been tested using sEMG measurements as control data on three different walking patterns: normal walk, fast walk and stair climbing. Estimated knee torque area and measured muscular activity for each step were compared confirming a high estimation accuracy with a correlation efficient R=0.80. Moreover, muscular activity can be divided based on intensity in three groups of statistically significant difference confirmed by the Steel-Dwass method. Future works should test the usability of the algorithm for different walking patterns, and use the collected data and the refined algorithm to implement a smart resistive device to increase knee extensor exertion during each walking pattern to the level necessary for sufficient extensor training.

Evaluation of a Sensor System for Detecting Humans Trapped under Rubble: A Pilot Study

Rapid localization of injured survivors by rescue teams to prevent death is a major issue. In this paper, a sensor system for human rescue including three different types of sensors, a CO₂ sensor, a thermal camera, and a microphone, is proposed. The performance of this system in detecting living victims under the rubble has been tested in a high-fidelity simulated disaster area. Results show that the CO₂ sensor is useful to effectively reduce the possible concerned area, while the thermal camera can confirm the correct position of the victim. Moreover, it is believed that the use of microphones in connection with other sensors would be of great benefit for the detection of casualties. In this work, an algorithm to recognize voices or suspected human noise under rubble has also been developed and tested.

Anatomical Calibration through Post-Processing of Standard Motion Tests Data

The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method.

Heel-Contact Toe-Off Walking Pattern Generator Based on the Linear Inverted Pendulum

We propose a novel heel-contact toe-off walking pattern generator for a biped humanoid robot. It is divided in two stages: a simple model stage where a Linear Inverted Pendulum (LIP) based heel-contact toe-off walking model based on the so-called functional rockers of the foot (heel, ankle and forefoot rockers) is used to calculate step positions and timings, and the Center of Mass (CoM) trajectory taking step lengths as inputs, and a multibody dynamics model stage, where the final pattern to implement on the humanoid robot is obtained from the output of the first simple model stage. The final pattern comprises the Zero Moment Point (ZMP) reference, the joint angle references and the end effector references. The generated patterns were implemented on our robotic platform, WABIAN-2R to evaluate the generated walking patterns.

Quantitative Laughter Detection, Measurement, and Classification-A Critical Survey

The study of human nonverbal social behaviors has taken a more quantitative and computational approach in recent years due to the development of smart interfaces and virtual agents or robots able to interact socially. One of the most interesting nonverbal social behaviors, producing a characteristic vocal signal, is laughing. Laughter is produced in several different situations: in response to external physical, cognitive, or emotional stimuli; to negotiate social interactions; and also, pathologically, as a consequence of neural damage. For this reason, laughter has attracted researchers from many disciplines. A consequence of this multidisciplinarity is the absence of a holistic vision of this complex behavior: the methods of analysis and classification of laughter, as well as the terminology used, are heterogeneous; the findings sometimes contradictory and poorly documented. This survey aims at collecting and presenting objective measurement methods and results from a variety of different studies in different fields, to contribute to build a unified model and taxonomy of laughter. This could be successfully used for advances in several fields, from artificial intelligence and human-robot interaction to medicine and psychiatry.

A novel approach to low cost, wide range motion capture system: Validation and application to human behavior analysis

From new hardware arise possibilities to develop novel methods of monitoring human behavior. In this paper we present a low cost system using two RGB-D cameras in a 3m × 8m space. Using developed software, we are able to easily collect, combine, visualize, modify, and analyze data. To validate the system, we measured human behavior in a walking experiment (N = 11). The data obtained from the system showed an accurate measurement and validated our approach for Human Interaction analysis.

Angular sway propagation in One Leg Stance and quiet stance with Inertial Measurement Units for older adults

Postural stability degrades with age, threating the health and life quality of the older adults. One Leg Stance (OLS) is one of the standard and commonly adopted assessments for postural stability, and the postural sway in OLS has been demonstrated to be related with age. The propagation of postural sway between body segments could be a hint to the underlying mechanism of balance control. However, it is not yet fully understood. Therefore, the aim of this paper was to study the angular sways and their propagation of the head, trunk, and lower limb in healthy older adults. A cross-correlation of the normalized angular speeds was performed and the experiment with 68 older adults was conducted. The results showed that the head, hip and ankle joints affected the transfer of angular sway with a relatively lower correlation and longer latency.

Objective evaluation of oral presentation skills using Inertial Measurement Units

Oral presentation is considered as one of the most sought after skills by companies and professional organizations and program accreditation agencies. However, both learning process and evaluation of this skill are time demanding and complex tasks that need dedication and experience. Furthermore, the role of the instructor is fundamental during the presentation assessment. The instructor needs to consider several verbal and nonverbal communications cues sent in parallel and this kind of evaluation is often subjective. Even if there are oral presentation rubrics that try to standardize the evaluation, they are not an optimal solution because they do not provide the presenter a real-time feedback. In this paper, we describe a system for behavioral monitoring during presentations. We propose an ecological measurement system based on Inertial Measurement Units to evaluate objectively the presenter's posture through objective parameters. The system can be used to provide a real-time feedback to the presenters unobtrusively.

On Stereo Confidence Measures for Global Methods: Evaluation, New Model and Integration into Occupancy Grids

Stereo confidence measures are important functions for global reconstruction methods and some applications of stereo. In this article we evaluate and compare several models of confidence which are defined at the whole disparity range. We propose a new stereo confidence measure to which we call the Histogram Sensor Model (HSM), and show how it is one of the best performing functions overall. We also introduce, for parametric models, a systematic method for estimating their parameters which is shown to lead to better performance when compared to parameters as computed in previous literature. All models were evaluated when applied to two different cost functions at different window sizes and model parameters. Contrary to previous stereo confidence measure benchmark literature, we evaluate the models with criteria important not only to winner-take-all stereo, but also to global applications. To this end, we evaluate the models on a real-world application using a recent formulation of 3D reconstruction through occupancy grids which integrates stereo confidence at all disparities. We obtain and discuss our results on both indoors' and outdoors' publicly available datasets.

Behavior modulation of rats to a robotic rat in multi-rat interaction

In this paper, we study the behavioral response of rats to a robotic rat during multi-rat interaction. Experiments are conducted in an open-field where a robotic rat called WR-5 is put together with three laboratory rats. WR-5 is following one rat (target), while avoiding the other two rats (outside observers) during interaction. The behavioral characteristics of each target rat is evaluated by scoring its locomotor activity and frequencies of performing rearing, body grooming and mounting actions. Additionally, the frequency of being mounted by other rats is also measured. Experimental results show that the target becomes more active after interaction. The rat species, with more active behavioral characteristics, is more susceptible to being adjusted by the robot. The increased time spent by the outside observers in the vicinity of the robot indicates that a biomimetic robot has the promise for modulating rat behavior even without direct interaction. Thus, this study provide a novel approach to shaping the sociality of animals living in groups.

Human abdomen recognition using camera and force sensor in medical robot system for automatic ultrasound scan

Physicians use ultrasound scans to obtain real-time images of internal organs, because such scans are safe and inexpensive. However, people in remote areas face difficulties to be scanned due to aging society and physician's shortage. Hence, it is important to develop an autonomous robotic system to perform remote ultrasound scans. Previously, we developed a robotic system for automatic ultrasound scan focusing on human's liver. In order to make it a completely autonomous system, we present in this paper a way to autonomously localize the epigastric region as the starting position for the automatic ultrasound scan. An image processing algorithm marks the umbilicus and mammary papillae on a digital photograph of the patient's abdomen. Then, we made estimation for the location of the epigastric region using the distances between these landmarks. A supporting algorithm distinguishes rib position from epigastrium using the relationship between force and displacement. We implemented these algorithms with the automatic scanning system into an apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator. Tests on 14 healthy male subjects showed the apparatus located the epigastric region with a success rate of 94%. The results suggest that image recognition was effective in localizing a human body part.

Use of an ultra-miniaturized IMU-based motion capture system for objective evaluation and assessment of walking skills

The increasing age of the world population is posing new challenges to our society, such as how to keep this aging population healthy and active despite of the age. In recent years, there has been a lot of interest for gait analysis for rehabilitation purposes as well as for performance assessment of this aging population. While current systems work well, they still have several limitations. Cost, need for specialized personnel, need to be used in a research center, and sporadic measurement prevent these systems from being widely used. The authors propose the use of extremely miniaturized, portable measurement systems, which can be worn by the users during their everyday life, and can monitor their gait over a long timespan. This paper presents the preliminary experiments with such a system.

The influences of emotional intensity for happiness and sadness on walking

Walking is one of the most common activities that we perform every day. Even if the main goal of walking is to move from one place to another place, walking can also convey emotional clues in social context. Those clues can be used to improve interactions or any messages we want to express. However, there are not many studies on the effects of the intensity of the emotions on the walking. In this paper, the authors propose to assess the differences between the expression of emotion regarding the expressed intensity (low, middle, high and exaggerated). We observed two professional actors perform emotive walking, with different intensities and we analyzed the recorded data. For each emotion, we analyzed characteristic features which can be used in the future to model gait patterns and to recognize emotions from the gait parameters. Additionally, we found characteristics which can be used to create new emotion expression for our biped robot Kobian, improving the human-robot interaction.

Reliability of the step phase detection using inertial measurement units: pilot study

The use of inertial sensors for the gait event detection during a long-distance walking, for example, on different surfaces and with different walking patterns, is important to evaluate the human locomotion. Previous studies demonstrated that gyroscopes on the shank or foot are more reliable than accelerometers and magnetometers for the event detection in case of normal walking. However, these studies did not link the events with the temporal parameters used in the clinical practice; furthermore, they did not clearly verify the optimal position for the sensors depending on walking patterns and surface conditions. The event detection quality of the sensors is compared with video, used as ground truth, according to the parameters proposed by the Gait and Clinical Movement Analysis Society. Additionally, the performance of the sensor on the foot is compared with the one on the shank. The comparison is performed considering both normal walking and deviations to the walking pattern, on different ground surfaces and with or without constraints on movements. The preliminary results show that the proposed methodology allows reliable detection of gait events, even in case of abnormal footfall and in slipping surface conditions, and that the optimal location to place the sensors is the shank.

Walking in the uncanny valley: importance of the attractiveness on the acceptance of a robot as a working partner

The Uncanny valley hypothesis, which tells us that almost-human characteristics in a robot or a device could cause uneasiness in human observers, is an important research theme in the Human Robot Interaction (HRI) field. Yet, that phenomenon is still not well-understood. Many have investigated the external design of humanoid robot faces and bodies but only a few studies have focused on the influence of robot movements on our perception and feelings of the Uncanny valley. Moreover, no research has investigated the possible relation between our uneasiness feeling and whether or not we would accept robots having a job in an office, a hospital or elsewhere. To better understand the Uncanny valley, we explore several factors which might have an influence on our perception of robots, be it related to the subjects, such as culture or attitude toward robots, or related to the robot such as emotions and emotional intensity displayed in its motion. We asked 69 subjects (N = 69) to rate the motions of a humanoid robot (Perceived Humanity, Eeriness, and Attractiveness) and state where they would rather see the robot performing a task. Our results suggest that, among the factors we chose to test, the attitude toward robots is the main influence on the perception of the robot related to the Uncanny valley. Robot occupation acceptability was affected only by Attractiveness, mitigating any Uncanny valley effect. We discuss the implications of these findings for the Uncanny valley and the acceptability of a robotic worker in our society.

Biologically-Inspired Control Architecture for Musical Performance Robots

At Waseda University, since 1990, the authors have been developing anthropomorphic musical performance robots as a means for understanding human control, introducing novel ways of interaction between musical partners and robots, and proposing applications for humanoid robots. In this paper, the design of a biologically-inspired control architecture for both an anthropomorphic flutist robot and a saxophone playing robot are described. As for the flutist robot, the authors have focused on implementing an auditory feedback system to improve the calibration procedure for the robot in order to play all the notes correctly during a performance. In particular, the proposed auditory feedback system is composed of three main modules: an Expressive Music Generator, a Feed Forward Air Pressure Control System and a Pitch Evaluation System. As for the saxophone-playing robot, a pressure-pitch controller (based on the feedback error learning) to improve the sound produced by the robot during a musical performance was proposed and implemented. In both cases studied, a set of experiments are described to verify the improvements achieved while considering biologically-inspired control approaches.

Development of new muscle contraction sensor to replace sEMG for using in muscles analysis fields

Nowadays, the technologies for detecting, processing and interpreting bioelectrical signals have improved tremendously. In particular, surface electromyography (sEMG) has gained momentum in a wide range of applications in various fields. However, sEMG sensing has several shortcomings, the most important being: measurements are heavily sensible to individual differences, sensors are difficult to position and very expensive. In this paper, the authors will present an innovative muscle contraction sensing device (MC sensor), aiming to replace sEMG sensing in the field of muscle movement analysis. Compared with sEMG, this sensor is easier to position, setup and use, less dependent from individual differences, and less expensive. Preliminary experiments, described in this paper, confirm that MC sensing is suitable for muscle contraction analysis, and compare the results of sEMG and MC sensor for the measurement of forearm muscle contraction.

Application of wireless inertial measurement units and EMG sensors for studying deglutition - Preliminary results

Different types of sensors are being used to study deglutition and mastication. These often suffer from problems related to portability, cost, reliability, comfort etc. that make it difficult to use for long term studies. An inertial measurement based sensor seems a good fit in this application; however its use has not been explored much for the specific application of deglutition research. In this paper, we present a system comprised of an IMU and EMG sensor that are integrated together as a single system. With a preliminary experiment, we determine that the system can be used for measuring the head-neck posture during swallowing in addition to other parameters during the swallowing phase. The EMG sensor may not always be a reliable source of physiological data especially for small clustered muscles like the ones responsible for swallowing. In this case, we explore the possibility of using gyroscopic data for the recognition of deglutition events.

Study of Bipedal Robot Walking Motion in Low Gravity: Investigation and Analysis

Humanoid robots are expected to play a major role in the future of space and planetary exploration. Humanoid robot features could have many advantages, such as interacting with astronauts and the ability to perform human tasks. However, the challenge of developing such a robot is quite high due to many difficulties. One of the main difficulties is the difference in gravity. Most researchers in the field of bipedal locomotion have not paid much attention to the effect of gravity. Gravity is an important parameter in generating a bipedal locomotion trajectory. This research investigates the effect of gravity on bipedal walking motion. It focuses on low gravity, since most of the known planets and moons have lower gravity than earth. Further study is conducted on a full humanoid robot model walking subject to the moon's gravity, and an approach for dealing with moon gravity is proposed in this paper.

Modulation of rat behaviour by using a rat-like robot

In this paper, we study the response of a rat to a rat-like robot capable of generating different types of behaviour (stressful, friendly, neutral). Experiments are conducted in an open-field where a rat-like robot called WR-4 is put together with live rats. The activity level of each rat subject is evaluated by scoring its locomotor activity and frequencies of performing rearing (rising up on its hind limbs) and body grooming (body cuddling and head curling) actions, whereas the degree of preference of that is indicated by the robot-rat distance and the frequency of contacting WR-4. The moving speed and behaviour of WR-4 are controlled in real-time based on the feedback from rat motion. The activity level and degree of preference of rats for each experimental condition are analysed and compared to understand the influence of robot behaviour. The results of this study show that the activity level and degree of preference of the rat decrease when exposed to a stressful robot, and increase when the robot exhibit friendly behaviour, suggesting that a rat-like robot can modulate rat behaviour in a controllable, predictable way.

Safe venepuncture techniques using a vacuum tube system

The purpose of this study was to determine safe techniques of performing blood collection using an evacuated tube system, particularly with regard to manipulation of the equipment and at the puncture site. Careful observation of the procedure was used to collect data for evaluating the various venepuncture techniques. Nurses were digitally videotaped performing simulated venepuncture. A self-administered questionnaire and unstructured observation of a videotaped recording were evaluated, and valid responses were analyzed from participants who performed venepuncture using various techniques. The participants who changed hands during the procedure were older than those who did not change hands. Needle movements during puncture and insertion, including rotation and insertion in a wave-like trajectory, were observed. Appropriate training, including recommendations for maintaining the stability of the needle tip, is important to ensure safety when performing venepuncture. Movement of the needle should not place too much pressure on the puncture site.

Development of an objective endoscopic surgical skill assessment system for pediatric surgeons: suture ligature model of the crura of the diaphragm in infant fundoplication

BACKGROUND AND AIM

The Japanese Society of Pediatric Endoscopic Surgeons developed an endoscopic surgical skill qualification (ESSQ) system. However, this is a subjective system we developed and validated an objective skill evaluation system for pediatric surgeons.

METHODS

In the ESSQ system, the task operation is laparoscopic fundoplication. Therefore, we set up a suture ligature model of the crura of the diaphragm for infant fundoplication. Examinees were divided into 2 groups, 10 experts and 16 trainees. They had to perform two suture ligatures of the crura using an intracorporeal knot in the box. Evaluation points were time, force on the tissue, suture tension, stitch spacing, equidistance, mean score, and total score. Statistical analysis was performed and p < 0.05 was considered statistically significant.

RESULTS

Experts showed better score than trainees in the time score (p < 0.0001), the score for force on the tissue (p < 0.0001), the stitch spacing score (p < 0.05), the equidistance score (p < 0.005), the mean score (p < 0.0001), and the total score (p < 0.0005), respectively.

CONCLUSION

The results revealed that the expert group possessed gentle and speedy skills compared with that of the novices. Using this validation study, our established model could be used to objectively evaluate the endoscopic surgical skills of pediatric surgeons.

Biomechanical evaluation of the phases during simulated endotracheal intubation (ETI): pilot study on the effect of different laryngoscopes

Endotracheal Intubation (ETI) is a common airway procedure used to connect the larynx and the lungs through a windpipe in patients under emergency situations. The process is carried out by a laryngoscope inserted into the mouth, used to help doctors in visualizing the glottis and inserting the tube. Currently, very few studies on objective evaluation of the biomechanics of the doctors during the procedure have been done. Additionally, these studies have been concentrated only on the overall performance analysis, without any segmentation, with a consequent loss of important information. In this paper, the authors present a preliminary study on a methodology to objectively evaluate and segment the biomechanical performance of doctors during the ETI, using surface electromyography and inertial measurement units. In particular, the validation has been performed by comparing three kinds of laryngoscopes involving an expert doctor. Finally, results are presented and commented.

Objective skill evaluation for laparoscopic training based on motion analysis

Performing laparoscopic surgery requires several skills, which have never been required for conventional open surgery. Surgeons experience difficulties in learning and mastering these techniques. Various training methods and metrics have been developed to assess and improve surgeon's operative abilities. While these training metrics are currently widely being used, skill evaluation methods are still far from being objective in the regular laparoscopic skill education. This study proposes a methodology of defining a processing model that objectively evaluates surgical movement performance in the routine laparoscopic training course. Our approach is based on the analysis of kinematic data describing the movements of surgeon's upper limbs. An ultraminiaturized wearable motion capture system (Waseda Bioinstrumentation system WB-3), therefore, has been developed to measure and analyze these movements. The data processing model was trained by using the subjects' motion features acquired from the WB-3 system and further validated to classify the expertise levels of the subjects with different laparoscopic experience. Experimental results show that the proposed methodology can be efficiently used both for quantitative assessment of surgical movement performance, and for the discrimination between expert surgeons and novices.

Gait Phase Detection Using Foot Acceleration for Estimating Ground Reaction Force in Long Distance Gait Rehabilitation

In gait rehabilitation, achieving a gait analysis method using a simple system during long-distance walking is important. This method is required to measure all gait parameters in a single measurement. In addition, it is required that the measurement system is not spatially constrained. Therefore, we have been developing a gait tracking system with acceleration sensors for long-distance gait rehabilitation. In this paper, we describe a gait phase detection method using foot acceleration data for estimating ground reaction force during long-distance gait rehabilitation. To develop this method, we focused on the jerk of each foot in vertical axis direction. Using two accelerometers mounted on the left and right feet, we carried out three experiments. First, we measured the jerk of each foot during a free gait to verify the relation with the walking speed. Second, we measured the jerk of each foot during walking faster than normal for each subject. We then compared these results with the results of first experiments. Finally, we measured the jerk of each foot during left-right asymmetrical walking. The results confirmed that gait phase could be detected using the jerk of each leg, calculated from acceleration data in vertical axis direction. In particular, the timing of Heel-contact / Toe-off could be obtained with an average error of 0.03 s. And as a preliminary study, we estimated the ground reaction force using the one of the results.

Development of the wireless ultra-miniaturized inertial measurement unit WB-4: preliminary performance evaluation

This paper presents the preliminary performance evaluation of our new wireless ultra-miniaturized inertial measurement unit (IMU) WB-4 by compared with the Vicon motion capture system. The WB-4 IMU primarily contains a mother board for motion sensing, a Bluetooth module for wireless data transmission with PC, and a Li-Polymer battery for power supply. The mother board is provided with a microcontroller and 9-axis inertial sensors (miniaturized MEMS accelerometer, gyroscope and magnetometer) to measure orientation. A quaternion-based extended Kalman filter (EKF) integrated with an R-Adaptive algorithm for automatic estimation of the measurement covariance matrix is implemented for the sensor fusion to retrieve the attitude. The experimental results showed that the wireless ultra-miniaturized WB-4 IMU could provide high accuracy performance at the angles of roll and pitch. The yaw angle which has reasonable performance needs to be further evaluated.