Handwriting Correction System using Wearable Sleeve with Optimal Tactor Configuration

Handwriting remains an elusive skill with practice worksheets being the common method of learning. Since these worksheets provide only visual feedback and no quantitative feedback, it can often be a challenge to improve. For children with learning disabilities, learning handwriting skills is one of the most difficult tasks. We propose a handwriting training system that uses off-the-shelf webcam, a pen tracking software and a haptic sleeve which provides active feedback to the user based on their deviation from the original pattern. The sleeve has 4 individual motors that vibrate at different intensities based on the direction (right, left, up or down) and severity of the deviation (\u3c 1cm, 1cm – 3cm, \u3e 3cm). Different motor placements around the forearm are evaluated for vibro-tactile feedback accuracy and time response, and a novel spaced-ring configuration is proposed. This paper provides details on the system architecture and sleeve characterization, and the results show promise in utilizing the system for self-correction and visual-motor skills development. The results from sleeve characterization suggest the applicability of the spaced-ring configuration (perceived feedback accuracy \u3e 98%, time response \u3c 1s) in other vibrotactile hand guidance systems, in addition to handwriting correction. Recommendations on tactor placements around the forearm are provided

Scalability of the Size of Patterns Drawn Using Tactile Hand Guidance

Haptic feedback for handwriting training has been extensively studied, but with primary focus on kinematic feedback. We provide vibrotactile feedback through a wrist worn sleeve to guide the user to recreate unknown patterns and study the impact of vibrational duration (1, 2, 3 seconds) on pattern scaling. User traces a line at 90° angles, while attempting to maintain a constant speed, in the direction of the motor activated till a different motor activation is perceived. Shape and size are two features of good letter formation. Study performed on three subjects showed the ability to utilize four vibrotactile motors to guide the hand towards correct shape formation with high accuracy (\u3e 95%). The overall size of the letter was observed to scale linearly with the vibrational duration. Implications for utilizing the vibrational feedback for handwriting correction are discussed

Can You Ink While You Blink? Assessing Mental Effort in a Sensor-Based Calligraphy Trainer

Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the expert model to provide guidance and feedback to the learners. However, new learners can be overwhelmed by the feedback as handwriting learning is a tedious task. This paper presents the pilot study done with the calligraphy trainer to evaluate the mental effort induced by various types of feedback provided by the application. Ten participants, five in the control group and five in the treatment group, who were Ph.D. students in the technology-enhanced learning domain, took part in the study. The participants used the application to learn three characters from the Devanagari script. The results show higher mental effort in the treatment group when all types of feedback are provided simultaneously. The mental efforts for individual feedback were similar to the control group. In conclusion, the feedback provided by the calligraphy trainer does not impose high mental effort and, therefore, the design considerations of the calligraphy trainer can be insightful for multimodal feedback designers