HaloSense V1 turns a detected direction into a tactile pointer: it estimates direction with a compass or camera, selects one of 13 vibration motors arranged around a headband, and activates that motor. The maker’s Arduino UNO Q prototype demonstrates screen-free directional feedback in three modes—compass, person detection, and printed-marker tracking—but it is an experimental build, not a validated navigation or accessibility aid.
How can a headband use vibration motors to show direction without a screen?
The basic idea is to convert an angle into a place on the wearer’s forehead. HaloSense V1’s 13 motors form a semicircular haptic ring. Once the system estimates where a target lies relative to the wearer, its controller maps that direction to a motor position and activates the motor there. The wearer feels a localized vibration rather than reading a display.
This is directional feedback, not a complete description of the surroundings: a cue indicates the direction selected by the active mode, not distance, identity, or a safe route. The project author, pasquale887, describes the concept as sensing north, people, or targets without looking down. Read the HaloSense V1 project description.
What do HaloSense V1’s three modes do?
Compass: point toward magnetic north
An LSM303DLHC magnetometer and accelerometer provide heading information. The STM32 maps the heading to one of the 13 motor positions, so the vibration indicates the direction of magnetic north. This is a compass cue; it should not be mistaken for a camera-based target or a tested turn-by-turn navigation system.
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Person: cue a detected person in the camera view
Two USB webcams provide images to the UNO Q’s Linux side, where the project stitches the frames and runs YOLOX-Nano person detection. The software estimates the person’s horizontal angle and sends a motor selection to the microcontroller. The visual modes are described as covering an approximately 120-degree forward arc, rather than the wearer’s full surroundings.
Target: cue a printed ArUco marker
In target mode, OpenCV detects a printed ArUco marker and maps its horizontal position in the camera view to the haptic ring. The maker also demonstrates a separate interaction: when a marker is centered and an external controller is touched, the system triggers a TP-Link Tapo P100 smart plug. That demonstration depends on the marker and controller; it is not an additional general-purpose sensing mode.
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How the UNO Q divides the work
The project assigns camera capture, computer vision, and a web dashboard to the UNO Q’s Linux side. Its STM32 side handles the PCA9685 motor-driver interface and compass loop, and receives motor selections from Linux through Arduino’s Bridge. This division matches the UNO Q’s architecture: Arduino describes the board as combining a Debian Linux Qualcomm QRB2210 MPU with an STM32U585 MCU and an RPC Bridge between them. Arduino UNO Q documentation.
The rest of the documented setup includes a PCA9685 16-channel PWM driver, two ULN2803 arrays, 13 ERM vibration motors, an LSM303DLHC/GY-511 sensor breakout, two USB webcams, and a separate ESP32 NodeMCU WROOM-32D controller. The author describes each motor as having its own switched return line and the motors sharing a positive rail.
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For the assembly, the maker lists a 5V 3A wall adapter as the main power supply and a 5V 2.1A power bank as an alternative. These are the author’s stated build options, not independently verified electrical recommendations or runtime comparisons. The project does not identify an exact ERM motor model, so a similarly named motor should not be assumed compatible without checking its electrical requirements and physical fit.
What the prototype’s performance reports establish—and what they do not
The maker reports that the two webcam streams ran at around 30 FPS and that the haptic response had no perceptible lag in their build. These are personal observations, not independent benchmarks; they do not establish detection accuracy, end-to-end latency under other conditions, or how the system performs across users and environments.
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The camera modes depend on what the cameras can see. The approximately 120-degree forward visual field reported for the build does not provide all-around awareness, and camera view and surroundings can affect detection. A person or marker outside the visible area cannot be represented by that camera pipeline.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What HaloSense V1 is—and is not
The documented version is an experimental assembly on a semicircular foam-and-rubber ring with fabric and a Velcro strap. The motors are hot-glued around the ring; cameras and the sensor sit in separate 3D-printed mounts. It combines multiple motors, cameras, cabling, and electronics, rather than presenting as a compact everyday wearable.
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The available project account and coverage do not establish clinical validation, an independent user study, measured accessibility outcomes, or independently measured directional accuracy. Accordingly, HaloSense V1 is best understood as a maker prototype demonstrating one way to encode selected directions as touch—not as a proven navigation aid, medical device, or finished consumer product. BLE angle-of-arrival positioning, a flexible PCB, and EEG-based intention detection are ideas the maker lists for possible future work, not capabilities of V1. Circuit Digest’s coverage also describes the prototype and its limitations.
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