Grammar-Dependent Tactile Pattern Invocation for Remote Telepresence
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Solution Overview
Problem
Current remote tactile telepresence systems face challenges with high latency and usability, particularly in conveying complex tactile interactions over networks, which affects the consistency and efficiency of haptic experiences between users.
Innovation Solution
The system employs a touchscreen interface to detect tactile inputs, which are recognized by a gesture recognizer and matched to unique profiles in a database. These profiles are transmitted to a remote network, where they are used to activate haptic devices, and can be linked to visual indicia or alphanumeric strings, allowing for efficient communication and synchronization of tactile sensations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gesture patterns are transmitted in full detail over the network, then tactile sensation accuracy is improved, but network bandwidth consumption increases and latency increases
Solution Approach 1:
The gesture pattern data is segmented into essential and non-essential components. Only the essential parameters needed to reproduce the tactile sensation are transmitted over the network, while non-essential details are omitted or compressed. This segmentation allows accurate tactile reproduction with reduced data transmission, thereby lowering latency and bandwidth consumption.
Solution Approach 2:
Instead of transmitting the complete gesture pattern data, a simplified copy or representation of the essential gesture characteristics is transmitted. The receiving system reconstructs the full tactile sensation from this compressed representation, achieving accurate tactile reproduction with minimal data transmission and reduced latency.
2Reliability
If complex gesture patterns are transmitted in detail, then tactile interaction fidelity is improved, but network bandwidth consumption increases
Solution Approach 1:
Complex gesture patterns are segmented into core tactile parameters and auxiliary details. Only the core parameters essential for faithful tactile reproduction are transmitted over the network, while auxiliary details are either omitted or reconstructed locally. This maintains tactile interaction fidelity while significantly reducing bandwidth consumption.
Solution Approach 2:
The system transforms complex gesture pattern data into a reduced parameter set that captures the essential tactile characteristics. By changing the representation from full-detail spatial-temporal data to a compact parameter encoding, the system achieves high fidelity tactile transmission with minimal bandwidth usage.
3Adaptability or versatility
If custom gesture patterns are created and transmitted, then tactile expression versatility is improved, but processing overhead increases
Solution Approach 1:
The system implements a universal gesture pattern framework where a standardized set of base gesture templates can be combined and modified to create diverse tactile expressions. This universal approach allows versatile tactile communication while avoiding the processing overhead of creating and managing entirely custom gesture patterns for each interaction.
Solution Approach 2:
Common gesture patterns are pre-defined and stored in a local database on both transmitting and receiving devices. When a gesture needs to be transmitted, the system performs a quick match against the pre-existing database rather than processing and creating the gesture pattern in real-time. This preliminary preparation significantly reduces processing overhead while maintaining tactile expression versatility.
4Speed
If a local database of gesture patterns is maintained, then gesture recognition speed is improved, but device memory consumption increases
Solution Approach 1:
The gesture pattern database is segmented into frequently used and rarely used categories. Only the most frequently used gesture patterns are stored locally in memory for rapid recognition, while less common patterns are stored remotely or generated on-demand. This segmentation achieves fast gesture recognition for common interactions while minimizing device memory consumption.
Data Source
AI summary
A system for translating text streams of alphanumeric characters into preconfigured, haptic output. Text strings are parsed against a grammar index to locate assigned haptic or vibratory output. This may include speech-to-text, chat messaging, or text arrays of any kind. When a match is located, a standardized haptic output pattern is invoked through a haptic device. A device affordance module adapts the haptic output pattern to the capabilities of the target haptic device.


