Tadahisa Kondo

Phonological deficit and the reliance on orthographic approximation for reading: a follow-up study on an English-Japanese bilingual with monolingual dyslexia

A follow-up study was conducted on AS, previously reported as an English-Japanese bilingual with monolingual phonological dyslexia in English (Wydell and Butterworth, 1999). It was hypothesised that ASs fundamental deficit which lead to his dyslexia in English would still persist despite him successfully taking a BSc course in an English-speaking country. AS and his Japanese and English control participants were asked to read aloud a target stimulus first, and then to decide whether the target was a word or nonword. Unlike the control participants, AS showed a marked dissociation between his performance in the lexical (orthographic and phonological) decision and the word naming tasks. Often those words and pseudo-homophones (e.g. neym), which AS read erroneously, were correct in the decision tasks – the target pseudo-homophone or word was substituted by another orthographically similar word. The results thus demonstrated that his reading of unfamiliar words or nonwords is essentially based on orthographic approximation using the visual similarities between words. The results confirmed the earlier finding that AS has a core phonological deficit which led to his dyslexia but never affected his reading in Japanese. The results also confirmed that this deficit persists when reading in English. This implies that whatever the neurological abnormality that AS may have, this only affects certain languages, and this abnormality persists with time.

Visibility analysis for autonomous vehicle comfortable navigation.

This work introduces a 3D visibility model for comfortable autonomous vehicles. The model computes a visibility index based on the pose of the wheelchair within the environment. We correlate this index with human navigational comfort (discomfort) and we discuss the importance of modeling visibility to improve human riding comfort. The proposed approach models the 3D visual field of view combined with a two-layered environmental representation. The field of view is modeled with information from the pose of the robot, a 3D laser sensor and a two-layered environmental representation composed of a 3D geometric map with traversale area information. Human navigational discomfort was extracted from participants riding the autonomous wheelchair. Results show that there is fair correlation between poor visibility locations (e.g., blind corners) and human discomfort. The approach can model places with identical traversable characteristics but different visibility and it differentiates visibility characteristics according to traveling direction.

Modeling of human velocity habituation for a robotic wheelchair.

This work proposes a model for human habituation while riding a robotic wheelchair. We present and describe the concept of human navigational habituation which we define as the human habituation to repetitively riding a robotic wheelchair. The approach models habituation in terms of preferred linear velocity based on the experience of riding a wheelchair. We argue that preferred velocity changes as the human gets used to riding on the wheelchair. Inexperienced users initially prefer to ride at a slow moderate pace, however the longer they ride they prefer to speed up to a certain comfort level and find initial slower velocities to be tediously “too slow” for their experience level. The proposed habituation model provides passenger preferred velocity based on experience. Human biological measurements, galvanic skin conductance, and participant feedback demonstrate the preference for habituation velocity control over fixed velocity control. To our knowledge habituation modeling is new in the field of autonomous navigation and robotics.

Robotic service coordination for elderly people and caregivers with Ubiquitous Network Robot Platform

This paper proposed a method for deploying robotic service coordination for elderly people and caregivers. By showing two kinds of robotic services for them in real environments, we explain what important designs to deploy robotic services are. For this purpose, we utilized an infrastructure, called Ubiquitous Network Robot Platform (UNR-PF), allowing robot service coordination with robots, smartphones, and sensor networks. Three layered architecture of UNR-PF supports developers of personalized robotic services and their coordination to utilize different types of hardware according to characteristics of users. In the case studies of elderly care, robotic services should consider different types of hardware (e.g., wheelchair type) due to characteristics of users; it makes difficulties for design of robotics services.

Behavioral and neuroimaging research of reading: A case of Japanese

Behavioral studies showed that AS, an English-Japanese bilingual, was a skilled reader in Japanese but was a phonological dyslexic in English. This behavioral dissociation was accounted for by the Hypothesis of Transparency and Granularity postulated by Wydell and Butterworth. However, a neuroimaging study using magnetoencephalography (MEG) revealed that AS has the same functional deficit in the left superior temporal gyrus (STG). This paper therefore offers an answer to this intriguing discrepancy between the behavioral dissociation and the neural unity in AS by reviewing existing behavioral and neuroimaging studies in alphabetic languages such as English, Finnish, French, and Italian, and nonalphabetic languages such as Japanese and Chinese.

Driving behavior analysis using vision-based head pose estimation for enhanced communication among traffic participants

We propose a scheme to evaluate driver behaviors by a vision-based head pose estimation method. In our project, we are investigating a collaborative safety mechanism based on the mutual sharing of driver information (attention and performance) in daily situations. The analysis of driver behaviors based on a non-contact type of measurement is one key issue in our mechanism. In this paper, we describe a voting-based head pose estimation algorithm and several driving behavior analysis results using our method. We also address examples of graphical representations for driver information sharing that directly correspond to the extracted driving behaviors.