Intention Reading is Essential in Human-Friendly Interfaces for the Elderly and the Handicapped

Bien, Zeungnam; Park, Kwang‐Hyun; Jung, Jin‐Woo; Do, Jun-Hyeong

doi:10.1109/tie.2005.858734

Cited by 33 publications

(13 citation statements)

References 8 publications

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“…Additionally, in this system there is no need to draw straight lines which is difficult for motor impairment users [30], because lines with some curves are also accepted as a result of the thickening process. So this method can be used to create man-machine interfaces which are easier for human users and more users -including elderly and disabled userscan use them [31].…”

Section: Discussionmentioning

confidence: 99%

Multilingual Highlighting CAPTCHA

Shirali-Shahreza

2011

2011 Eighth International Conference on Information Technology: New Generations

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There are many websites specially designed for mobile phones. Some hackers write automated programs to abuse these website services and waste the website resources. Therefore, it is necessary to distinguish between human users and computer programs. Methods known for achieving this are known as CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart). CAPTCHA methods are mainly based on the weaknesses of OCR (Optical Character Recognition) systems and ask the user to type a word. So using them is difficult in tools such as PDAs (Personal Digital Assistant) or mobile phones that lack a complete keyboard.In this paper, a new CAPTCHA system is proposed for touchscreen devices such as PDAs and mobile phones. In this system, a word is drawn in a random place on the screen and a number of arcs are drawn on the screen. Then the user is asked to highlight the word by the stylus. Due to the limitations of the PDA and mobile phone, OCR programs on these devices cannot recognize the shown word, while a human user can easily highlight the word. The proposed method is implemented by the JavaME (Java Platform Micro Edition) language and tested on a SonyEricsson P990i mobile phone.

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Section: Discussionmentioning

confidence: 99%

Multilingual Highlighting CAPTCHA

Shirali-Shahreza

2011

2011 Eighth International Conference on Information Technology: New Generations

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“…A recurrent issue is related to the difficulty to identify gestures, vocal inputs and others which are not intended to trigger any interaction with the machine (talking to someone else, taking a drink, moving, etc.). Consequently, one limiting factor of current HCIs is the detection of the intention of the user with respect to the multimedia device [8]. Solving this problem would lead to devices that "know" when you are addressing an order to them and thus would allow much more natural interactions (no/less false alarms on gestures/words not directed to the machine).…”

Section: Introductionmentioning

confidence: 99%

Virtual interactions: Can EEG Help Make the Difference with Real Interaction?

Rzepecki

Delcourt

Silva

et al. 2012

2012 IEEE International Conference on Multimedia and Expo Workshops

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Science and technology progress fast, but mouse and keyboard are still used to control multimedia devices. One of the limiting factors of gesture based HCIs adoption is the detection of the user's intention to interact. This study tries to make a step in that direction with use of consumer EEG sensor headset. EEG headset records in real-time data that can help to identify intention of the user based on his emotional state. For each subject EEG responses for different stimuli are recorded. Acquiring these data allows to determine the potential of EEG based intention detection. The findings are promising and with proper implementation should allow to building a new type of HCI devices.

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“…Research uses force/ torque-, tactile-and vision-sensors for human motions sensing [2][3][4][5][6][7] has flourished in the past several decades. Particularly in cooperative machine research, a machine has been shown to interpret measured force as an operator intention and then carry objects for the operator [8].…”

Section: Introductionmentioning

confidence: 99%

Real-time upper limb motion prediction from noninvasive biosignals for physical human-machine interactions

Kwon

Kim

2009

2009 IEEE International Conference on Systems, Man and Cybernetics

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Human motion and its intention sensing from noninvasive biosignals is one of the significant issues in the field of physical human-machine interactions (pHMI). This paper presents a real-time upper limb motion prediction method using surface electromyography (sEMG) signals for pHMI. The sEMG signals from 5 channels were collected and used to predict the motion by an artificial neural network (ANN) algorithm. We designed a human-machine interaction system to verify the proposed method. Interaction experiments were performed with or without physical contact, and the effects of instances of contact were investigated. The experimental results were compared with controlled experiments using a customized goniometer, which is able to measure upper limb flexion-extension. The results showed that the proposed method was not superior to the use of direct angle measurements; however, it provides sufficient accuracy and a fast response speed for interactions. SEMG-based interactions will become more natural with further studies of human-machine combination models.

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Intention Reading is Essential in Human-Friendly Interfaces for the Elderly and the Handicapped

Cited by 33 publications

References 8 publications

Multilingual Highlighting CAPTCHA

Multilingual Highlighting CAPTCHA

Virtual interactions: Can EEG Help Make the Difference with Real Interaction?

Real-time upper limb motion prediction from noninvasive biosignals for physical human-machine interactions

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