RIZZOLABS

A person holds a smartphone while navigating a subway station. The screen displays real-time sign detection and transit information overlaid on the camera view. The system reads station signs and provides auditory guidance using OCR and GTFS data to support middle-mile navigation for people with visual impairments.

A person extends their arm and points toward objects in a room. A wearable device tracks the 3D pointing gesture and announces the identified object aloud. The system reduces cognitive load by enabling hands-free, gesture-based object identification for visually impaired users.

A person walks while wearing a haptic belt around their waist. the walkable space is detected by the camera, the belt vibrates in the direction of least amount of obstacles. The wearable system delivers depth-based vibrotactile feedback to support open-path navigation without vision.

A person navigates through an urban environment while wearing a camera-based system. The device performs visual place recognition to estimate position and heading without fixed GPS infrastructure. On-screen overlays show topometric mapping and navigation guidance derived from the live camera feed.

A wearable camera system detects curbs and step edges as a person walks on a sidewalk. Real-time vision-based segmentation identifies elevation changes ahead. The system delivers auditory warnings and orientation cues before the user reaches the curb, improving pedestrian safety for people with visual impairments.

A person walks through a city block where construction is present. The system camera feed shows bounding boxes drawn around construction barriers, equipment, and signage detected in real time using YOLO models. OCR reads warning signs and announces hazard information to the user via audio.

A person navigates a store aisle while holding a smartphone. The ShopScout system detects product labels, reads barcodes, and uses spatial audio cues to guide the shopper toward target items. Vision-language models provide product descriptions, enabling independent shopping for people with visual impairments.

A participant performs a standardized hand function task at a table while wearing eye-tracking glasses. Motion capture markers on the hand and objects record movement kinematics. The system extracts objective eye-hand coordination and movement-quality biomarkers for rehabilitation assessment.

A child's hands are shown performing a dexterity task such as placing pegs on a board. Computer vision algorithms detect and track finger movements and object interactions in real time. The system extracts objective hand function metrics beyond simple task completion time for pediatric rehabilitation assessment.

A person performs a standardized dexterity task under camera observation. The system tracks hand and finger movements using object detection and pose estimation. Objective metrics capturing movement strategy and quality are extracted to assess motor impairment associated with Multiple Sclerosis.