Haptic communication system using cutaneous actuators for simulation of continuous human touch
摘要
說明書
The processor circuit 232 may include a machine learning circuit 242 communicating with the feature extraction component 236 to determine a touch signature of the sending user based on the extracted features 244 and automatically encode the touch signature into the haptic illusion signals 202. The touch signatures may be represented as a vector of values for each defined word of a social touch lexicon. For qualitative models, this touch signature vector may include values 0 or 1.
In one embodiment, the feature extraction component 236 extracts features from a user profile of the receiving user. The machine learning circuit 242 may further determine a score for the generated haptic illusion signals 202 based on the extracted features. The score may indicative of a likelihood of the receiving user expressing a preference for the haptic illusion signals 202 based on the user profile.
In one embodiment, the processor circuit 232 determines an affinity between the sending user and the receiving user, and modifies the haptic illusion signals 202 based on the determined affinity. For example, the processor circuit 232 may alter generic haptic illusion signals for “Greeting” to be reflective of a more intimate relationship between the first and receiving users if the affinity between them reflects that they are partners. In one embodiment, the processor circuit 232 retrieves a user profile of the receiving user, and modifies the haptic illusion signals 202 based on the retrieved user profile. For example, the processor circuit 232 may alter the haptic illusion signals 202 to be gentler (i.e., weaker) if the receiving user is of the female gender.
