11 research outputs found

    Comparison of gait event detection from shanks and feet in single-task and multi-task walking of healthy older adults

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    Automatic and objective detection algorithms for gait events from MEMS Inertial Measurement Units data have been developed to overcome subjective inaccuracy in traditional visual observation. Their accuracy and sensitivity have been verified with healthy older adults, Parkinson's disease and spinal injured patients, using single-task gait exercises, where events are precise as the subject is focusing only on walking. Multi-task walking instead simulates a more realistic and challenging scenario where subjects perform secondary cognitive task while walking, so it is a better benchmark. In this paper, we test two algorithms based on shank and foot angular velocity data in single-task, dual-task and multi-task walking. Results show that both algorithms fail when the subject slows extremely down or pauses due to high cognitive and attentional load, and, in particular, the first stride detection error rate of the foot-based algorithm increases. Stride time is accurate with both algorithms regardless of walking types, but the shank-based algorithm leads to an overestimation on the proportion of swing phase in one gait cycle. Increasing the number of cognitive tasks also causes this error with both algorithms

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

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    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

    Bipedal humanoid robot that makes humans laugh with use of the method of comedy and affects their psychological state actively

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    This paper describes the bipedal humanoid robot that makes human laugh with its whole body expression and affect human’s psychological state. In order to realize "Social interaction" between human and robot, the robot has to affect human’s psychological state actively. We focused on "laugh" because it can be thought as a typical example for researching "Social interaction". Looking through a Japanese comedy style called "manzai" or the art of conversation, we picked out several methods for making human laugh. Then we made several skits with the advice of comedians, and made the whole body humanoid robot perform them. Results of experimental evaluation with these skits shows that the robot’s behavior made subjects laugh and change their psychological state seen as a decrease of "Depression" and "Anger"

    System integration: development of a global network communication protocol

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    In the era of globalization and standardization, in the perspective of industrial system integration, the implementation of a network framework able to interconnect any type of device and supporting both real-time (RT) and time-uncritical communication is becoming a must. This paper proposes an original entirely software-based communication framework to support RT communication over standard Ethernet, and compares it with the most relevant commercially available RT protocols in term of global costs and performances. ©2010 IEEE

    Natural human-robot musical interaction: understanding the music conductor gestures by using the WB-4 inertial measurement system

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    This paper presents an IMU (Inertial Measurement Unit) based human gesture recognition system for a robot instrument player to understand the instructions dictated by an orchestra conductor and accordingly adapt its musical performance. It is an extension of our previous publications on natural human-robot musical interaction [28]. With this system, the robot can understand the real- time variations in musical parameters dictated by the conductor's movements, adding expression to its performance while being synchronized with all the other human partner musicians. The enhanced interaction ability would obviously lead to an improvement of the overall live performance, but also allow the partner musicians, as well as the conductor, to better appreciate a joint musical performance, thanks to the complete naturalness of the interaction

    Bipedal humanoid robot that makes humans laugh with use of the method of comedy and affects their psychological state actively

    No full text
    This paper describes the bipedal humanoid robot that makes human laugh with its whole body expression and affect human’s psychological state. In order to realize "Social interaction" between human and robot, the robot has to affect human’s psychological state actively. We focused on "laugh" because it can be thought as a typical example for researching "Social interaction". Looking through a Japanese comedy style called "manzai" or the art of conversation, we picked out several methods for making human laugh. Then we made several skits with the advice of comedians, and made the whole body humanoid robot perform them. Results of experimental evaluation with these skits shows that the robot’s behavior made subjects laugh and change their psychological state seen as a decrease of "Depression" and "Anger"

    The Italy–Japan workshop: A history of bilateral cooperation, pushing the boundaries of robotics

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    This article presents the experience of a longlasting collaboration in robotics between the countries of Japan and Italy. The diversity of the approaches to robotics research and technology in the two countries and, at the same time, the similarity of some social drives for robotics progress have created a stimulus for generating new thinking about robotics. Not only has this occurred at the main participant institutions of Waseda University in Tokyo and Scuola Superiore Sant?Anna in Pisa, Italy, but it has also happened worldwide. The authors present a summary of the Italy-Japan workshops, exploring topics on 1) humanoid robotics, 2) the application of robotics for exploration and rescue, 3) biorobotics, 4) the use of robots in education, 5) the ethics of robotics, 6) robotics for sports, and 7) robotics for the arts. The experience of the workshops represents an example of an open-minded approach to robotics that is grounded on social challenges, explored through multidisciplinary discussion. Such interdisciplinary research efforts deserve to be shared with the international robotics community. Indeed, this approach could be used as a base model to foster further international collaborations among countries as well

    Comparison of gait event detection from shanks and feet in single-task and multi-task walking of healthy older adults

    No full text
    Automatic and objective detection algorithms for gait events from MEMS Inertial Measurement Units data have been developed to overcome subjective inaccuracy in traditional visual observation. Their accuracy and sensitivity have been verified with healthy older adults, Parkinson's disease and spinal injured patients, using single-task gait exercises, where events are precise as the subject is focusing only on walking. Multi-task walking instead simulates a more realistic and challenging scenario where subjects perform secondary cognitive task while walking, so it is a better benchmark. In this paper, we test two algorithms based on shank and foot angular velocity data in single-task, dual-task and multi-task walking. Results show that both algorithms fail when the subject slows extremely down or pauses due to high cognitive and attentional load, and, in particular, the first stride detection error rate of the foot-based algorithm increases. Stride time is accurate with both algorithms regardless of walking types, but the shank-based algorithm leads to an overestimation on the proportion of swing phase in one gait cycle. Increasing the number of cognitive tasks also causes this error with both algorithms

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

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    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

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

    No full text
    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
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