These Amazing Wearable Projects Let You Bring DIY Tech Everywhere

The miniaturization of electronics has ushered in an era of unprecedented connectivity and data collection, as highly mobile sensors and IoT devices can now be placed almost anywhere. And with these new capabilities, the maker community has been creating helpful projects that do everything from displaying useful information to collecting health data in hopes of spotting problems before they crop up. So join us as we celebrate Wearable Tech Month here on Hackster.io by viewing some of our favorite portable technology projects.

Alzheimer's Assistant

Alzheimer's is an extremely destructive disease that destroys the very essence of oneself by degrading memory and thinking abilities. Because 1 in 9 people aged 65 and above suffer from it, Abdullah Sadiq decided to build an assistive smartwatch that displays basic reminders, shows the time, monitors the wearer's location, and can even alert caretakers in the event of an emergency. It works by using an Infineon Sensor Hub in conjunction with an Arduino MKR1000 board to read sensor information and send it to either a smartphone or to an IoT platform.

Arduglasses

Arduboy's Kevin Bates designed the Arduglasses as a way to showcase custom Arduboy games running in a novel form factor. The frame is fashioned from a set of PCBs that contain an ATmega32U4 microcontroller along with a small joystick for entering inputs. The star of the show, however, is the pair of transparent OLED panels in the front that make the lenses, resulting in a set of futuristic glowing glasses.

nRF53-powered smartwatch

Sindre Havoland's smartwatch is a DIY recreation of the Apple Watch that attempts to integrate a variety of sensors for a much lower cost than the real thing. His design revolves around an nRF53 SoC that sits on the primary PCB next to a microphone and a BMP680 gas sensing module. The color IPS screen can show several useful data points, and the built-in wireless charging pad underneath is a quick way to recharge without the need for a cable.

Memory Pill

Similar to the previously mentioned Alzheimer's Assistant, the Memory Pill project by Nick Bild aims to help seniors know when they last took their medications to avoid accidental over- or under-doses. Whenever the user removes the top of the medication bottle, a small button gets released and changes the state of an Arduino Nano 33 IoT's pin. From here, a timestamp is sent to a remote web API, which can be read by a mobile watch app in the future.

Assistive technology for the blind

Life for those who are blind can be quite dangerous, owing to busy street crossings, hidden obstacles, and more. In response, Salman Faris and Suhail Jr. worked together to build a pair of smart glasses they call Sight. The glasses are made of a Raspberry Pi 3 and a camera module, which gather images and process them using TensorFlow to recognize objects. The team's application then reads out these findings to the user with text-to-speech.

Distance monitor

At the start of the pandemic, nearly everyone was concerned about keeping adequate distance between one another in hopes of slowing the spread of COVID-19. The Corona Wearable Distance Monitor by Random Stuff We Make! and Sahil Rastogi set out to automate this check by constantly checking how close objects in front appeared. The circuit, made of an ESP8266 board, ultrasonic distance sensor, ring of LEDs, and a battery, is worn as a medallion.

Turning a glove into a computer mouse

The humble computer mouse has existed for several decades now with limited variations on how they function. The Smart Glove, made by Cameron Coward, is an attempt to introduce more novelty to this human interface device, which supports basic movements and clicking with either the left or right button. Movement is monitored with an accelerometer and sent to the host computer over USB, whereas clicks are detected with a pair of flex sensors.

watchX

Getting started with compact, embedded technology is tough for most hobbyists and even some professionals, which is what inspired palyancodr to develop the watchX platform. This multipurpose wearable can be programmed with the Arduino IDE, Atmel Studio, and even the block-based Scratch language. The watch integrates a 128x64 OLED screen, Bluetooth connectivity, and a variety of sensors and inputs devices. Best of all, it is easy to expand the functionality with either new hardware components or changes to the software.

Multimeter glasses

Multimeters are one of the fundamental tools used by everyone from electricians to electrical engineers, but having to move your attention back and forth to the screen while focusing on a part can be tough. Alain Mauer was able to view this data on a smart glasses add-on by integrating a tiny OLED screen and Arduino Micro Pro into them. The multimeter wirelessly sends values as small, coded packets over Bluetooth to an awaiting Bluetooth 4.0 module.

Translating sign language into text

The goal of this glove-based project, created by satyamkr80, Bipin Tiwari, and Swati Sharma, was to develop a system that could intelligently recognize sign language symbols performed by the user and translate them into readable text. A set of five bend sensors were placed over each finger/thumb joint on a glove and connected to an Arduino Nano board, which converts the analog values into digital ones and sends them over Bluetooth to a host device. Based on the values, the mobile app will display the corresponding letter to the viewer.

Nixie watch

The typical OLED screens we're used to seeing on smartwatches can get quite boring after a while, which is why Prototype Mechanic came up with a miniaturized clock that uses Nixie tubes to display the time. His project houses four Nixie tubes that can show both time and the date. Best of all, its battery lasts up to three months and can be recharged with a 5V USB power source.

Predicting seizures with machine learning

Around 1% of the US population suffers from seizures, and the anxiety surrounding when the next one might occur can be incredibly debilitating. Terry Rodriguez and Salma Mayorquin have built a wearable device that attempts to predict when the next seizure is likely through the power of machine learning. The pair trained a custom model using a 106GB dataset of previous seizure events, and by reading new data with a Mindwave Mobile headband into a Raspberry Pi Zero W, could generate almost real-time notifications.

HealthConnect IoT armband

Manivannan'sHealthConnect armband was born out of the early days of the COVID-19 pandemic where patients were unable to access their regular and frequent check-ups. His solution to this issue was to combine a heart rate monitor, SpO2 oxygen sensor, temperature sensor, and an accelerometer for fall detection into a single wearable device for constant health monitoring. In turn, this data was sent from a Microchip AVR-IoT WA development board to a secure AWS-powered monitoring webpage.

Tracking pet activity

Our pets' health is held up just as highly as our own for many of us, which means that ensuring they get enough exercise is vital for their well-being. Mithun Das'sPet Activity Tracker integrates embedded machine learning into a tiny, battery-powered module that can be easily attached to a dog's collar. Its XIAO BLE Sense module reads the accelerometer data, infers the current activity, and sends that data to a mobile phone for easy viewing.

Open source VR headset

Probably the most advanced project in this list, the Relativity device is an open source VR headset that supports SteamVR and even body-tracking through the use of a neural network that estimates 3D positions. The headset was made possible thanks to its dual 2K displays that can output images at 120 fps. All of the computational horsepower comes from an Microchip SAM3X8E Cortex-M3 processor mounted to a custom PCB along with an MPU-6050 IMU for motion tracking.

ExoMIND glove

The last glove in this list aims to assist in stroke rehabilitation by generating valuable data on the patient's progress. Built by a team of seven people from Purdue University, the ExoMIND glove uses a total of seven IMUs, with one placed at the end of each finger and two being placed on the forearm for tracking overall positioning. A single EMG sensor measures electrical activity from the wearer's muscles, and everything is read by an Arduino, which sends this data to a host application for further analysis.