  This paper presents an innovative feature signal transmission approach
incorpo-rating block-based haptic data reduction to address time-delayed
teleoperation. Numerous data reduction techniques rely on perceptual deadband
(DB). In the preceding block-based approaches, the whole block within the DB is
discarded. However, disregarding all signals within the DB loses too much
information and hinders effective haptic signal tracking, as these signals
contain valuable infor-mation for signal reconstruction. Consequently, we
propose a feature signal transmission approach based on the block algorithm
that aggregates samples as a unit, enabling high-quality haptic data reduction.
In our proposed approach, we employ max-pooling to extract feature signals from
the signals within the DB. These feature signals are then transmitted by
adjusting the content of the trans-mission block. This methodology enables the
transmission of more useful infor-mation without introducing additional delay,
aside from the inherent algorithmic delay. Experimental results demonstrate the
superiority of our approach over oth-er state-of-the-art (SOTA) methods on
various assessment measures under dis-tinct channel delays.
