Near Real-Time Data Labeling Using a Depth Sensor for EMG Based Prosthetic Arms

Recognizing sEMG (Surface Electromyography) signals belonging to a particular action (e.g., lateral arm raise) automatically is a challenging task as EMG signals themselves have a lot of variation even for the same action due to several factors. To overcome this issue, there should be a proper separation which indicates similar patterns repetitively for a particular action in raw signals. A repetitive pattern is not always matched because the same action can be carried out with different time duration. Thus, a depth sensor (Kinect) was used for pattern identification where three joint angles were recording continuously which is clearly separable for a particular action while recording sEMG signals. To Segment out a repetitive pattern in angle data, MDTW (Moving Dynamic Time Warping) approach is introduced. This technique is allowed to retrieve suspected motion of interest from raw signals. MDTW based on DTW algorithm, but it will be moving through the whole dataset in a pre-defined manner which is capable of picking up almost all the suspected segments inside a given dataset an optimal way. Elevated bicep curl and lateral arm raise movements are taken as motions of interest to show how the proposed technique can be employed to achieve auto identification and labelling. The full implementation is available at https://github.com/GPrathap/OpenBCIPytho

Model and implementation of body movement recognition using Support Vector Machines and Finite State Machines with cartesian coordinates input for gesture-based interaction

The growth in the use of gesture-based interaction in video games has highlighted the potential for the use of such interaction method for a wide range of applications. This paper presents the implementation of an enhanced model for gesture recognition as input method for software applications. The model uses Support Vector Machines (SVM) and Finite State Machines (FSM) and the implementation was based on a Kinect R device. The model uses data input based on Cartesian coordinates. The use of Cartesian coordinates enables more flexibility to generalise the use of the model to different applications, when compared to related work encountered in the literature based on accelerometer devices for data input. The results showed that the use of SVM and FSM with Cartesian coordinates as input for gesture-based interaction is very promising. The success rate in gesture recognition was 98%, from a training corpus of 9 sets obtained by recording real users’ gestures. A proof-of-concept implementation of the gesture recognition interaction was performed using the application Google Earth(R). A preliminary acceptance evaluation with users indicated that the interaction with the system via the implementation reported was satisfactory.Facultad de Informátic

Learning Algorithm Design for Human-Robot Skill Transfer

In this research, we develop an intelligent learning scheme for performing human-robot skills transfer. Techniques adopted in the scheme include the Dynamic Movement Prim- itive (DMP) method with Dynamic Time Warping (DTW), Gaussian Mixture Model (G- MM) with Gaussian Mixture Regression (GMR) and the Radical Basis Function Neural Networks (RBFNNs). A series of experiments are conducted on a Baxter robot, a NAO robot and a KUKA iiwa robot to verify the effectiveness of the proposed design.During the design of the intelligent learning scheme, an online tracking system is de- veloped to control the arm and head movement of the NAO robot using a Kinect sensor. The NAO robot is a humanoid robot with 5 degrees of freedom (DOF) for each arm. The joint motions of the operator’s head and arm are captured by a Kinect V2 sensor, and this information is then transferred into the workspace via the forward and inverse kinematics. In addition, to improve the tracking performance, a Kalman filter is further employed to fuse motion signals from the operator sensed by the Kinect V2 sensor and a pair of MYO armbands, so as to teleoperate the Baxter robot. In this regard, a new strategy is developed using the vector approach to accomplish a specific motion capture task. For instance, the arm motion of the operator is captured by a Kinect sensor and programmed through a processing software. Two MYO armbands with embedded inertial measurement units are worn by the operator to aid the robots in detecting and replicating the operator’s arm movements. For this purpose, the armbands help to recognize and calculate the precise velocity of motion of the operator’s arm. Additionally, a neural network based adaptive controller is designed and implemented on the Baxter robot to illustrate the validation forthe teleoperation of the Baxter robot.Subsequently, an enhanced teaching interface has been developed for the robot using DMP and GMR. Motion signals are collected from a human demonstrator via the Kinect v2 sensor, and the data is sent to a remote PC for teleoperating the Baxter robot. At this stage, the DMP is utilized to model and generalize the movements. In order to learn from multiple demonstrations, DTW is used for the preprocessing of the data recorded on the robot platform, and GMM is employed for the evaluation of DMP to generate multiple patterns after the completion of the teaching process. Next, we apply the GMR algorithm to generate a synthesized trajectory to minimize position errors in the three dimensional (3D) space. This approach has been tested by performing tasks on a KUKA iiwa and a Baxter robot, respectively.Finally, an optimized DMP is added to the teaching interface. A character recombination technology based on DMP segmentation that uses verbal command has also been developed and incorporated in a Baxter robot platform. To imitate the recorded motion signals produced by the demonstrator, the operator trains the Baxter robot by physically guiding it to complete the given task. This is repeated five times, and the generated training data set is utilized via the playback system. Subsequently, the DTW is employed to preprocess the experimental data. For modelling and overall movement control, DMP is chosen. The GMM is used to generate multiple patterns after implementing the teaching process. Next, we employ the GMR algorithm to reduce position errors in the 3D space after a synthesized trajectory has been generated. The Baxter robot, remotely controlled by the user datagram protocol (UDP) in a PC, records and reproduces every trajectory. Additionally, Dragon Natural Speaking software is adopted to transcribe the voice data. This proposed approach has been verified by enabling the Baxter robot to perform a writing task of drawing robot has been taught to write only one character

Machine Sensation

Emphasising the alien qualities of anthropomorphic technologies, Machine Sensation makes a conscious effort to increase rather than decrease the tension between nonhuman and human experience. In a series of rigorously executed cases studies, including natural user interfaces, artificial intelligence as well as sex robots, Leach shows how object-oriented ontology enables one to insist upon the unhuman nature of technology while acknowledging its immense power and significance in human life. Machine Sensation meticulously engages OOO, Actor Network Theory, the philosophy of technology, cybernetics and posthumanism in innovative and gripping ways

Kolab: Improvising Nomadic Tangible User Interfaces in the Workplace for Co-Located Collaboration

Tangible User Interfaces (TUIs) [Ishii 1997] offer an interface style that couples "digital information to everyday physical objects and environments" [Ishii 1997 page 2]. However this physicality may also be a limitation as the tendency to use iconic representations for tangibles can result in inflexible 'concrete and specialised objects' [Shaer 2009 page 107]. The current research investigates whether by reducing the dependence on specific tangible sets through the use of improvised tangibles we may begin to address the issue of tangible flexibility within TUIs. Improvised tangibles may be characterised by being potentially arbitrary and abstract, in that they may bear little or no resemblance to the underlying digital value. Core literature in the field (e. g. [Fitzmaurice 1996] [Ishii 2008] [Hornecker 2006] [Holmquist 1999]) suggests that a system based on improvised tangibles would suffer from impaired usability and so the research focuses on the impact on usability due to a lack of close representational significance [Ullmer 2000] during co-located collaboration. Using a prototyping methodology a functional, shareable, TUI system was developed based on computer vision techniques using the Microsoft Kinect [Microsoft2011]. This prototype system ('Kolab') was used to explore an interaction design that supports the dynamic binding of improvised tangibles to digital values. A simple co-located collaborative task was developed using 'Kolab' and a user study was conducted to investigate the usability of the system in a collaborative context. Within the limitations of the simple task the results of the study show that a) users appeared comfortable with improvising artefacts b) the high rate of task completion strongly suggests that a lack of close representational significance does not impair system usability and c) despite some temporary issues with users interfering with other's action an overall indication of equitable participation suggests that collaboration was not impaired by the 'Kolab' prototype

Introduction of novel interactive technologies into demanding healthcare contexts

The research described herein, conducted in pursuit of the academic qualification of Master of Philosophy (MPhil), follows two themes. The first, and overriding theme related to how the ergonomic and environmental challenges associated with the design, construction, and introduction of a series of iterative prototype technology solutions, capable of delivering Virtual Restorative Environments within a demanding healthcare arena. The research has been both human (patient)-centred and stakeholder-led from the outset (involving clinical and nursing specialists and advisors from the Queen Elizabeth Hospital Birmingham (QEHB)), and was undertaken with the support of early hardware and software grant funding from the Royal Centre for Defence Medicine (RCDM). The second, which is a guiding theme relates to how Virtual Restorative Environments (interactive 3D computer reconstructions of scenes of nature, such as forests, coastal paths and so on) can be exploited in hospital and related healthcare settings as a “tool” to promote mental restoration and rehabilitation, particularly following a traumatic incident, such as serious injury or surgery. What follows are a series of observational oriented studies (adhering closely to the ISO 9241-210 standard) that was conducted as an iterative pre-curser to a usability study that examined how patients, with varying degrees of injury coped with the use of a series of low cost control interfaces, combined with a prototype interaction module. Next it examined how the prototype technology can be iterated based on the evolving requirements of the stakeholder and a change in circumstances, to be re-deployed in a number of new environments to cater for different types of patient rehabilitation

Development and evaluation of a haptic framework supporting telerehabilitation robotics and group interaction

Telerehabilitation robotics has grown remarkably in the past few years. It can provide intensive training to people with special needs remotely while facilitating therapists to observe the whole process. Telerehabilitation robotics is a promising solution supporting routine care which can help to transform face-to-face and one-on-one treatment sessions that require not only intensive human resource but are also restricted to some specialised care centres to treatments that are technology-based (less human involvement) and easy to access remotely from anywhere. However, there are some limitations such as network latency, jitter, and delay of the internet that can affect negatively user experience and quality of the treatment session. Moreover, the lack of social interaction since all treatments are performed over the internet can reduce motivation of the patients. As a result, these limitations are making it very difficult to deliver an efficient recovery plan. This thesis developed and evaluated a new framework designed to facilitate telerehabilitation robotics. The framework integrates multiple cutting-edge technologies to generate playful activities that involve group interaction with binaural audio, visual, and haptic feedback with robot interaction in a variety of environments. The research questions asked were: 1) Can activity mediated by technology motivate and influence the behaviour of users, so that they engage in the activity and sustain a good level of motivation? 2) Will working as a group enhance users’ motivation and interaction? 3) Can we transfer real life activity involving group interaction to virtual domain and deliver it reliably via the internet? There were three goals in this work: first was to compare people’s behaviours and motivations while doing the task in a group and on their own; second was to determine whether group interaction in virtual and reala environments was different from each other in terms of performance, engagement and strategy to complete the task; finally was to test out the effectiveness of the framework based on the benchmarks generated from socially assistive robotics literature. Three studies have been conducted to achieve the first goal, two with healthy participants and one with seven autistic children. The first study observed how people react in a challenging group task while the other two studies compared group and individual interactions. The results obtained from these studies showed that the group interactions were more enjoyable than individual interactions and most likely had more positive effects in terms of user behaviours. This suggests that the group interaction approach has the potential to motivate individuals to make more movements and be more active and could be applied in the future for more serious therapy. Another study has been conducted to measure group interaction’s performance in virtual and real environments and pointed out which aspect influences users’ strategy for dealing with the task. The results from this study helped to form a better understanding to predict a user’s behaviour in a collaborative task. A simulation has been run to compare the results generated from the predictor and the real data. It has shown that, with an appropriate training method, the predictor can perform very well. This thesis has demonstrated the feasibility of group interaction via the internet using robotic technology which could be beneficial for people who require social interaction (e.g. stroke patients and autistic children) in their treatments without regular visits to the clinical centres

Videos in Context for Telecommunication and Spatial Browsing

The research presented in this thesis explores the use of videos embedded in panoramic imagery to transmit spatial and temporal information describing remote environments and their dynamics. Virtual environments (VEs) through which users can explore remote locations are rapidly emerging as a popular medium of presence and remote collaboration. However, capturing visual representation of locations to be used in VEs is usually a tedious process that requires either manual modelling of environments or the employment of specific hardware. Capturing environment dynamics is not straightforward either, and it is usually performed through specific tracking hardware. Similarly, browsing large unstructured video-collections with available tools is difficult, as the abundance of spatial and temporal information makes them hard to comprehend. At the same time, on a spectrum between 3D VEs and 2D images, panoramas lie in between, as they offer the same 2D images accessibility while preserving 3D virtual environments surrounding representation. For this reason, panoramas are an attractive basis for videoconferencing and browsing tools as they can relate several videos temporally and spatially. This research explores methods to acquire, fuse, render and stream data coming from heterogeneous cameras, with the help of panoramic imagery. Three distinct but interrelated questions are addressed. First, the thesis considers how spatially localised video can be used to increase the spatial information transmitted during video mediated communication, and if this improves quality of communication. Second, the research asks whether videos in panoramic context can be used to convey spatial and temporal information of a remote place and the dynamics within, and if this improves users' performance in tasks that require spatio-temporal thinking. Finally, the thesis considers whether there is an impact of display type on reasoning about events within videos in panoramic context. These research questions were investigated over three experiments, covering scenarios common to computer-supported cooperative work and video browsing. To support the investigation, two distinct video+context systems were developed. The first telecommunication experiment compared our videos in context interface with fully-panoramic video and conventional webcam video conferencing in an object placement scenario. The second experiment investigated the impact of videos in panoramic context on quality of spatio-temporal thinking during localization tasks. To support the experiment, a novel interface to video-collection in panoramic context was developed and compared with common video-browsing tools. The final experimental study investigated the impact of display type on reasoning about events. The study explored three adaptations of our video-collection interface to three display types. The overall conclusion is that videos in panoramic context offer a valid solution to spatio-temporal exploration of remote locations. Our approach presents a richer visual representation in terms of space and time than standard tools, showing that providing panoramic contexts to video collections makes spatio-temporal tasks easier. To this end, videos in context are suitable alternative to more difficult, and often expensive solutions. These findings are beneficial to many applications, including teleconferencing, virtual tourism and remote assistance