AquaScan, the first scanning sonar-based underwater sensing system for human activity monitoring. To
overcome the low frame rate due to the sonar’s physical
limitation, we propose a novel scanning strategy and apply
an image reconstruction method to accelerate the scanning
speed without compromising the performance of motion
detection
MyoTrainer is the first vision-based muscle-aware motion feedback system that uses explicit muscle-aware motion analysis and domain-specific expert knowledge to provide corrective guidance on muscle engagement and movement execution.
SmartLiDAR, an advanced LiDAR system that enhances scanning efficiency and performance by adaptively optimizing scan focus through an intelligent, softwaredefined micro-mirror controller. Unlike traditional systems, SmartLiDAR dynamically adjusts its scan pattern based on environmental characteristics and application-specific requirements, concentrating sample points on key objects without increasing power consumption or scan time.
This review conducts a bibliometric analysis of 431 studies from five major online databases, and provides a scoping review of 86 artificial intelligence (AI) models. Key focuses include motor activity, neurocognitive tests, eye tracking, and speech analysis.
SocialMind, the first LLM-based proactive AR social assistive system that provides users with in-situ social assistance. SocialMind employs human-like perception leveraging multi-modal sensors to extract both verbal and nonverbal cues, social factors, and implicit personas, incorporating these social cues into LLM reasoning for social suggestion generation.
TaskSense introduces a sensor language that automatically translates the capabilities and data dependencies of sensor systems into vocabularies and
grammar rules that can be understood by LLMs. It then interprets
user intentions into executable task plans for sensor systems using this sensor language in combination with LLMs.
SHADE-AD, a Large Language Model (LLM) framework for Synthesizing Human Activity Datasets Embedded with AD features. Leveraging both public datasets and our own collected data from 99 AD patients, SHADE-AD synthesizes human activity videos that specifically represent AD-related behaviors.
Argus, a wearable add-on system based
on stripped-down (i.e., compact, lightweight, low-power, limitedcapability) mmWave radars. It is the first to achieve egocentric human mesh reconstruction in a multi-view manner. Compared with
conventional frontal-view mmWave sensing solutions, it addresses
several pain points, such as restricted sensing range, occlusion, and
the multipath effect caused by surroundings.
Asteroid, a distributed edge training system that breaks the resource walls across heterogeneous edge devices for efficient model training acceleration. Asteroid adopts a hybrid pipeline parallelism to orchestrate distributed training, along with a judicious parallelism planning for maximizing throughput undercertain resource constraints.
The core concept of αLiDAR is to expand the operational freedom of a LiDAR sensor through the incorporation of a controllable, active rotational mechanism. This modification allows the sensor to scan previously inaccessible blind spots and focus on specific areas of interest in an adaptive manner.