Designing and Evaluating an Interface for the Composition of Vibro-Tactile Patterns Using Gestures

Real Time ◽

Sensory Substitution ◽

Motion System ◽

Computer Interfaces ◽

Art Form ◽

Substitution System ◽

Interface System ◽

Gesture Interfaces

Human-computer interaction systems have been providing new ways for amateurs to compose music using traditional computer peripherals as well as gesture interfaces. Vibro-tactile patterns, which are a vibrational art form similar to auditory music, can also be composed using human-computer interfaces. This thesis discusses the gesture interface system called the Vibro-Motion, which facilitates the composition of vibro-tactile patterns in real-time on an existing tactile sensory substitution system called the Emoti-Chair. The Vibro-Motion allows users to control the pitch, magnitude of the vibration as well as the position of the vibration. A usability evaluation of Vibro-Motion system showed it to be intuitive, comfortable and enjoyable for the participants.

A Real-Time Algorithm for Identifying Gait in a Sensory Substitution System

10.1109/urtc49097.2019.9660511 ◽

2019 ◽

Author(s):

Jamie E. Poole ◽

Jhon P. C. Casas ◽

Roberto A. Bolli ◽

Hermano I. Krebs

Keyword(s):

Real Time ◽

Time Algorithm ◽

Sensory Substitution ◽

Substitution System

Update of fNIRS as an Input to Brain–Computer Interfaces: A Review of Research from the Tufts Human–Computer Interaction Laboratory

Photonics ◽

10.3390/photonics6030090 ◽

2019 ◽

Vol 6 (3) ◽

pp. 90 ◽

Cited By ~ 2

Author(s):

Bosworth ◽

Russell ◽

Jacob

Keyword(s):

Real Time ◽

Near Infrared ◽

Brain Computer Interfaces ◽

Functional Near Infrared Spectroscopy ◽

The Past ◽

Computer Interfaces ◽

Brain States ◽

Over the past decade, the Human–Computer Interaction (HCI) Lab at Tufts University has been developing real-time, implicit Brain–Computer Interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS). This paper reviews the work of the lab; we explore how we have used fNIRS to develop BCIs that are based on a variety of human states, including cognitive workload, multitasking, musical learning applications, and preference detection. Our work indicates that fNIRS is a robust tool for the classification of brain-states in real-time, which can provide programmers with useful information to develop interfaces that are more intuitive and beneficial for the user than are currently possible given today’s human-input (e.g., mouse and keyboard).

Real-time spatial processing of sounds for music, multimedia and interactive human-computer interfaces

Multimedia Systems ◽

10.1007/s005300050111 ◽

1999 ◽

Vol 7 (1) ◽

pp. 55-69 ◽

Cited By ~ 26

Author(s):

Jean-Marc Jot

Keyword(s):

Real Time ◽

Spatial Processing ◽

Computer Interfaces ◽

Human Computer Interfaces

The Social And Interactional Dimensions Of Human-Computer Interfaces, edited by Peter J. Thomas, Cambridge Series on Human-Computer Interaction, CUP, Cambridge, 1995, 268 pages including contents and index (£35; Hbk)

Robotica ◽

10.1017/s0263574700019706 ◽

1996 ◽

Vol 14 (3) ◽

pp. 350-350

Author(s):

Iain A. Craig

Keyword(s):

Computer Interfaces ◽

The Social ◽

Human-Computer Interaction on Tabletops

Journal of Interactive Systems ◽

10.5753/jis.2011.577 ◽

2011 ◽

Vol 2 (2) ◽

pp. 1

Author(s):

Andreas M. Kunz

Keyword(s):

Computer Support ◽

Research Progress ◽

Future Research ◽

Ongoing Research ◽

Computer Interfaces ◽

Working Situation ◽

The most common working situation is standing or sitting at a table, and performing daily business work. Although this situation is very intuitive to the user, a computer support can hardly be found in this area, mainly because of missing or inadequate human-computer interfaces that do not meet the expected requirements of the user. However, ongoing research in this particular field of human-computer interaction addresses this problem. The following paper shows an exemplaric research progress and gives and outlook on future research.

Printed Texts Tracking and Following for a Finger-Wearable Electro-Braille System Through Opto-electrotactile Feedback

10.1101/2021.08.06.455412 ◽

2021 ◽

Author(s):

Mehdi Rahimi ◽

Yantao Shen ◽

Zhiming Liu ◽

Fang Jiang

Keyword(s):

Real Time ◽

Optical Character Recognition ◽

Text Processing ◽

Tactile Display ◽

Sensory Substitution ◽

Processing Unit ◽

Text Line ◽

Imaging Device ◽

Substitution System ◽

Printed Text

This paper presents our recent development on a portable and refreshable text reading and sensory substitution system for the blind or visually impaired (BVI), called Finger-eye. The system mainly consists of an opto-text processing unit and a compact electro-tactile based display that can deliver text-related electrical signals to the fingertip skin through a wearable and Braille-dot patterned electrode array and thus delivers the electro-stimulation based Braille touch sensations to the fingertip. To achieve the goal of aiding BVI to read any text not written in Braille through this portable system, in this work, a Rapid Optical Character Recognition (R-OCR) method is firstly developed for real-time processing text information based on a Fisheye imaging device mounted at the finger-wearable electro-tactile display. This allows real-time translation of printed text to electro-Braille along with natural movement of user's fingertip as if reading any Braille display or book. More importantly, an electro-tactile neuro-stimulation feedback mechanism is proposed and incorporated with the R-OCR method, which facilitates a new opto-electrotactile feedback based text line tracking control approach that enables text line following by user fingertip during reading. Multiple experiments were designed and conducted to test the ability of blindfolded participants to read through and follow the text line based on the opto-electrotactile-feedback method. The experiments show that as the result of the opto-electrotactile-feedback, the users were able to maintain their fingertip within a 2mm distance of the text while scanning a text line. This research is a significant step to aid the BVI users with a portable means to translate and follow to read any printed text to Braille, whether in the digital realm or physically, on any surface.

Four-Layer ConvNet to Facial Emotion Recognition with Minimal Epochs and the Significance of Data Diversity

10.20944/preprints202105.0424.v1 ◽

2021 ◽

Author(s):

Tanoy Debnath ◽

Md. Mahfuz Reza ◽

Anichur Rahman ◽

Shahab Band ◽

Hamid Alinejad Rokny

Keyword(s):

Emotion Recognition ◽

Real Time ◽

Emotional Processing ◽

Image Data ◽

Medical Diagnostics ◽

Computer Interfaces ◽

Proposed Model ◽

Fully Connected ◽

Better Than

Emotion recognition defined as identifying human emotion and is directly related to different fields such as human-computer interfaces, human emotional processing, irrational analysis, medical diagnostics, data-driven animation, human-robot communi- cation and many more. The purpose of this study is to propose a new facial emotional recognition model using convolutional neural network. Our proposed model, “ConvNet”, detects seven specific emotions from image data including anger, disgust, fear, happiness, neutrality, sadness, and surprise. This research focuses on the model’s training accuracy in a short number of epoch which the authors can develop a real-time schema that can easily fit the model and sense emotions. Furthermore, this work focuses on the mental or emotional stuff of a man or woman using the behavioral aspects. To complete the training of the CNN network model, we use the FER2013 databases, and we test the system’s success by identifying facial expressions in the real-time. ConvNet consists of four layers of convolution together with two fully connected layers. The experimental results show that the ConvNet is able to achieve 96% training accuracy which is much better than current existing models. ConvNet also achieved validation accuracy of 65% to 70% (considering different datasets used for experiments), resulting in a higher classification accuracy compared to other existing models. We also made all the materials publicly accessible for the research community at: https://github.com/Tanoy004/Emotion-recognition-through-CNN.

2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698) ◽

Real time eye tracking for human computer interfaces

10.1109/icme.2003.1221372 ◽

2003 ◽

Cited By ~ 14

Author(s):

S. Amarnag ◽

R.S. Kumaran ◽

J.N. Gowdy

Keyword(s):

Eye Tracking ◽

Real Time ◽

Computer Interfaces ◽

Human Computer Interfaces

The Machine Learning Algorithm as Creative Musical Tool

10.1093/oxfordhb/9780190226992.013.23 ◽

2018 ◽

Cited By ~ 1

Author(s):

Rebecca A. Fiebrink ◽

Baptiste Caramiaux

Keyword(s):

Machine Learning ◽

Learning Algorithm ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Machine Learning Algorithm ◽

Computational System ◽

Computer Interfaces ◽

Machine learning is the capacity of a computational system to learn structure from data in order to make predictions on new data. This chapter draws on music, machine learning, and human-computer interaction to elucidate an understanding of machine learning algorithms as creative tools for music and the sonic arts. It motivates a new understanding of learning algorithms as human-computer interfaces: like other interfaces, learning algorithms can be characterized by the ways their affordances intersect with goals of human users. The chapter also argues that the nature of interaction between users and algorithms impacts the usability and usefulness of those algorithms in profound ways. This human-centred view of machine learning motivates a concluding discussion of what it means to employ machine learning as a creative tool.