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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallHaloSense V1 turns an estimated direction into a localized vibration: it selects one of 13 motors arranged around a headband, so the wearer can feel a cue instead of looking at a screen. The maker’s experimental Arduino UNO Q prototype has three described modes—compass heading, person detection, and printed ArUco-marker tracking—but it is not a validated navigation aid or finished wearable.
How can a headband use vibration motors to show direction without a screen?
The system estimates a direction, maps that direction to a position on its motor ring, and activates the motor at that position. A vibration at a particular point around the forehead is the cue; the wearer does not need a display to see the selected direction.
In HaloSense V1, the ring has 13 eccentric rotating mass (ERM) vibration motors. The maker describes the arrangement as indicating magnetic north or the horizontal position of something seen by the cameras. This is a directional cue, not a complete instruction about where to walk or what to do.
What do HaloSense’s three modes detect?
COMPASS: magnetic heading
An LSM303DLHC accelerometer and magnetometer breakout supplies heading information. The STM32 maps the heading to one of the 13 motor positions. This mode indicates north relative to the headband; it does not use GPS or establish a route to a destination.
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- High-Resolution Altitude Tracking: 24-bit low-noise sensing enables precise vertical positioning for drones, GPS modules, and wearable devices, capturing subtle height changes in real-time.
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- Digital Output & Noise Filtering: On-chip signal processing filters out vibration and environmental noise, providing clean data for critical atmospheric calculations.
PERSON: a person in the camera view
Two USB webcams provide images to the UNO Q’s Linux side. The maker’s software stitches the camera frames, runs YOLOX-Nano person detection, estimates the detected person’s horizontal angle, and sends a selected motor index to the microcontroller. The selected motor is meant to indicate where the person appears across the forward camera view.
TARGET: an ArUco marker
In this mode, OpenCV detects a printed ArUco marker and maps its horizontal position to the motor ring. The maker also demonstrates a separate trigger: when a marker is centered and the external controller is touched, the setup activates a TP-Link Tapo P100 smart plug. That is a demonstration of a marker-triggered action, not a general-purpose smart-home feature.
The maker describes the visual modes as covering an approximately 120-degree forward arc. That leaves areas outside the camera view unrepresented, and detection depends on the camera image and surroundings. The cameras do not provide all-around awareness.
Rank #2
- 【6DOF COMPACT MOTION TRACKING】 Integrates a highly accurate accelerometer and gyroscope onto a space-saving IMU board to deliver orientation, tap detection, wake-up triggers, and real-time motion data
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- 【EVENT DRIVEN SENSING ENGINE】 Equipped with a built-in 9KB FIFO and programmable Finite State Machine (FSM) engine that manages buffered data and motion event checks for responsive project control
- 【READY EMBEDDED ACCESSORIES】 Comes as a complete development set ideal for wearable sensing, always-on IoT configurations, vibration analysis, and custom smart tracking projects requiring ready-to-use parts
How the UNO Q divides the work
The project uses the UNO Q’s Linux environment for camera capture, computer vision, and a web dashboard. Its STM32 side handles compass and motor control, with motor selections passed from Linux through the Bridge. Arduino describes the UNO Q as combining a Debian Linux Qualcomm QRB2210 MPU with an STM32U585 MCU and an RPC Bridge between them: Arduino UNO Q.
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In the maker’s build, the UNO Q works with a PCA9685 16-channel PWM driver, two ULN2803 arrays, 13 ERM motors, the LSM303DLHC/GY-511 sensor breakout, and two USB webcams. A separate ESP32 NodeMCU WROOM-32D serves as the external controller. The maker describes each motor as having its own switched return line and the motors sharing a positive rail; these are build details, not independent electrical verification.
What the V1 build is like—and what its performance claims mean
The documented headband is a semicircular foam-and-rubber ring covered with fabric and secured by a Velcro strap. The motors are hot-glued around it; the webcams and sensor use separate 3D-printed mounts. It is an experimental assembly with cameras, wiring, and electronics, not a compact everyday wearable.
The maker lists a 5V 3A wall adapter for the main assembly and a 5V 2.1A power bank as an alternative. Those are stated build options, not evidence about comparative runtime or battery life. The maker also reports that two webcam streams ran at around 30 FPS and that the haptic feedback had no perceptible lag in their build. These are personal observations, not independently benchmarked performance results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is HaloSense a proven navigation or accessibility device?
No. HaloSense V1 is presented as a personal experiment and a demonstration of screen-free directional feedback. The available coverage says it has not been clinically validated as an accessibility or navigation system; the material does not establish independent accuracy measurements, clinical evaluation, user-study results, or measured accessibility outcomes. A vibration cue that points toward a detected person or marker should not be treated as a safety-critical alert or as a substitute for established navigation tools.
The maker mentions BLE angle-of-arrival positioning, a flexible PCB, and EEG-based intention detection as possible future directions. Those are proposals, not capabilities of V1. The project’s primary description is available on Hackster; secondary coverage from Circuit Digest also describes the prototype and its limitations.
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