Abstract: Wearable robotics is a potential solution in aiding gait rehabilitation of lower limbs dyskinesia patients, such as knee osteoarthritis or stroke afflicted patients. Many wearable robots have been developed in the form of rigid exoskeletons, but their bulk devices, high cost and control complexity hinder their popularity in the field of gait rehabilitation. Thus, the development of a portable, compliant and low-cost wearable robot for gait rehabilitation is necessary. Inspired by Chinese traditional folding fans and balloon inflators, the authors present an inflatable, foldable and variable stiffness knee exosuit (IFVSKE) in this paper. The pneumatic actuator of IFVSKE was fabricated in the shape of folding fans by using thermoplastic polyurethane (TPU) fabric materials. The geometric and mechanical properties of IFVSKE were characterized with experimental methods. To assist the knee joint smartly, an intelligent control profile for IFVSKE was proposed based on the concept of full-cycle energy management of the biomechanical energy during human movement. The biomechanical energy of knee joints in a walking gait cycle of patients could be collected and released to assist the joint motion just by adjusting the inner pressure of IFVSKE. Finally, a healthy subject was involved to walk with and without the IFVSKE to evaluate the assisting effects.
Abstract: Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.
Abstract: Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.
Abstract: Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.
Abstract: The paper describes a Chinese shadow play animation
system based on Kinect. Users, without any professional training, can
personally manipulate the shadow characters to finish a shadow play
performance by their body actions and get a shadow play video
through giving the record command to our system if they want. In our
system, Kinect is responsible for capturing human movement and
voice commands data. Gesture recognition module is used to control
the change of the shadow play scenes. After packaging the data from
Kinect and the recognition result from gesture recognition module,
VRPN transmits them to the server-side. At last, the server-side uses
the information to control the motion of shadow characters and video
recording. This system not only achieves human-computer interaction,
but also realizes the interaction between people. It brings an
entertaining experience to users and easy to operate for all ages. Even
more important is that the application background of Chinese shadow
play embodies the protection of the art of shadow play animation.
Abstract: Human movement in the real world provides
important information for developing human behaviour models and
simulations. However, it is difficult to assess ‘real’ human behaviour
since there is no established method available. As part of the AUNTSUE
(Accessibility and User Needs in Transport – Sustainable Urban
Environments) project, this research aimed to propose a method to
assess human movement and behaviour in crowded areas. The
method is based on the three major steps of video recording,
conceptual behavior modelling and video analysis. The focus is on
individual human movement and behaviour in normal situations
(panic situations are not considered) and the interactions between
individuals in localized areas. Emphasis is placed on gaining
knowledge of characteristics of human movement and behaviour in
the real world that can be modelled in the virtual environment.
Abstract: The centre of rotation of the hip joint is needed for an
accurate simulation of the joint performance in many applications
such as pre-operative planning simulation, human gait analysis, and
hip joint disorders. In human movement analysis, the hip joint center
can be estimated using a functional method based on the relative
motion of the femur to pelvis measured using reflective markers
attached to the skin surface. The principal source of errors in
estimation of hip joint centre location using functional methods is
soft tissue artefacts due to the relative motion between the markers
and bone. One of the main objectives in human movement analysis is
the assessment of soft tissue artefact as the accuracy of functional
methods depends upon it. Various studies have described the
movement of soft tissue artefact invasively, such as intra-cortical
pins, external fixators, percutaneous skeletal trackers, and Roentgen
photogrammetry. The goal of this study is to present a non-invasive
method to assess the displacements of the markers relative to the
underlying bone using optical motion capture data and tissue
thickness from ultrasound measurements during flexion, extension,
and abduction (all with knee extended) of the hip joint. Results show
that the artefact skin marker displacements are non-linear and larger
in areas closer to the hip joint. Also marker displacements are
dependent on the movement type and relatively larger in abduction
movement. The quantification of soft tissue artefacts can be used as a
basis for a correction procedure for hip joint kinematics.
Abstract: The design of an active leg orthosis for tumble
protection is proposed in this paper. The orthosis would be applied to
assist elders or invalids in rebalancing while they fall unexpectedly.
We observe the regain balance motion of healthy and youthful people,
and find the difference to elders or invalids. First, the physical model
of leg would be established, and we consider the leg motions are
achieve through four joints (phalanx stem, ankle, knee, and hip joint)
and five links (phalanges, talus, tibia, femur, and hip bone). To
formulate the dynamic equations, the coordinates which can clearly
describe the position in 3D space are first defined accordance with the
human movement of leg, and the kinematics and dynamics of the leg
movement can be formulated based on the robotics. For the purpose,
assisting elders and invalids in avoiding tumble, the posture variation
of unbalance and regaining balance motion are recorded by the
motion-capture image system, and the trajectory is taken as the desire
one. Then we calculate the force and moment of each joint based on
the leg motion model through programming MATLAB code. The
results would be primary information of the active leg orthosis design
for tumble protection.
Abstract: Based on experimental data using accelerometry technology there was developed an analytical model that approximates human induced ground reaction forces in vertical, longitudinal and lateral directions ascending and descending the stairs. Proposed dynamic loading factors and corresponding phase shifts for the first five harmonics of continuous walking force history in case of stair ascend and descend. Into account is taken imperfectness of individual footfall forcing functions, differences between continuous walking force histories among individuals. There is proposed mean synthetic continuous walking force history that can be used in numerical simulations of human movement on the stairs.