Human-Computer Interface Technologies for the Motor Impaired

Human Computer Interface Technologies for the Motor Impaired examines both the technical and social aspects of human computer interface (HCI). Written by world-class academic experts committed to improving HCI technologies for people with disabilities, this all-inclusive book explores the latest research, and offers insight into the current limitations of this field. It introduces the concept of HCI, identifies and describes the fundamentals associated with a specific technology of HCI, and provides examples for each. It also lists and highlights the different modalities (video, speech, mechanical, myoelectric, electro-oculogram, and brain-waves) that are available, and discusses their relevant applications. Easily and readily understood by researchers, engineers, clinicians, and the common layperson, the book describes a number of HCI technologies ranging from simple modification of the computer mouse and joystick to a brain–computer interface (BCI) that uses the electrical recording of the brain activity of the user. The text includes photographs or illustrations for each device, as well as references at the end of each chapter for further study. In addition, this book: Describes the mechanical sensors that are used as an interface to control a computer or screen for the aged and disabled Discusses the BCI using brain waves recorded by noninvasive electrodes to recognize the command from the user Presents the myoelectric interface for controlling devices such as the prosthetic/robotic hand Explains the technology of tracking the eye gaze using video Provides the fundamentals of voice recognition technologies for computer and machine control applications Examines a secure and voiceless method for the recognition of speech-based commands using video of lip movement Human Computer Interface Technologies for the Motor Impaired considers possible applications, discusses limitations, and presents the current research taking place in the field of HCI. Dedicated to enhancing the lives of people living with disabilities, this book aids professionals in biomedical, electronics, and computer engineering, and serves as a resource for anyone interested in the developing applications of HCI.

IntroductionAbstractIntroduction: Human–computer interface for people with disabilitiesBackgroundHistoryFuture of HCILayout of the bookReferenceHuman–computer interface: Mechanical sensorsAbstractIntroductionModified devicesSensorsApplications of HCI based on mechanical sensorsCurrent research and future improvementsReferencesBrain–computer interface based on thought wavesAbstractIntroductionHistory of brain–computer interfaceSignificance of BCI devicesBCI technologySystem designSignal analysisBCI translation algorithmsUser considerationApplications of BCILimitationsFuture researchEthical considerationReferencesEvoked potentials-based brain–computer interfaceAbstractIntroductionBrain–computer interface (BCI) systems based on steady-state visual evoke potentialDesign challenges and limitationsResultsUser benefits and improvementsReferencesMyoelectric-based hand gesture recognition for human–computer interface applicationsAbstractIntroductionBackgroundCurrent technologies and implementationReferencesVideo-based hand movement for human–computer interfaceAbstractIntroductionBackgroundData analysisDiscussionUser requirementsUser benefitsShortcomingsFuture developmentsReferencesHuman–computer interface based on electrooculographyAbstractIntroductionBackgroundCurrent technologies: Historical to state of the artExample of EOG-based systemResultsDiscussionLimitations of the studyDiscussion: User benefits and limitationsReferencesFurther readingVideo-based eye trackingAbstractIntroductionBackground and historyAn example eye-tracking methodData analysisResultsDiscussion: User benefits and limitationsReferencesSpeech for controlling computersAbstractIntroductionHistory of speech-based machine commandsAutomatic speech recognition (ASR)Speech denoising methodsSpeech analysis fundamentalsSubsections of speech: PhonemesHow people speak: Speech production modelPlace principle hearing modelFeatures selection for speech analysisSpeech feature classificationArtificial neural networksLimitations in current systemsReferencesLip movement for human–computer interfaceAbstractIntroduction: History and applicationsCurrent technologiesUser requirementsExample of voiceless speech recognition systemsDiscussion: User benefitsSummaryReferences

Dinesh K. Kumar received a B.Tech from IIT Madras, and a Ph.D in biomedical engineering from IIT Delhi and AIIMS, Delhi. He is a professor and leader of biomedical engineering at RMIT University, Melbourne, Australia. Dr. Kumar has published more than 330 refereed papers in the field, and his interests include muscle control, affordable diagnostics, and human–computer interface. He is editor of multiple journals, chairs a range of conferences related to biomedical engineering, and enjoys walking in nature in his spare time. Sridhar Poosapadi Arjunan received a B.Eng in electronics and communication from the University of Madras, India; a M.Eng in communication systems from Madurai Kamaraj University, India; and a Ph.D in biomedical signal processing from RMIT University, Australia. He is currently a postdoctoral research fellow with Biosignals Lab at RMIT University. Dr. Poosapadi Arjunan is a recipient of the RMIT SECE Research Scholarship, CASS Australian Early Career Researcher Grant, and the Australia-India ECR Fellowship. His major research interests include biomedical signal processing, rehabilitation study, fractal theory, and human–computer interface applications.