Final Design

1 – The Central Electronics Hub houses all the main components. It utilizes Thermoplastic Polyurethane (TPU) material for its flexibility and impact-resistance.

2 – Lithium Ion batteries have high energy density while maintaining a small form factor.  

3 – A custom printed circuit board is employed to achieve a small footprint. All the electrical components are connected to

this PCB. The IMU #1 and ESP 32 are soldered into the board while three Tactilus sensors, IMU #2 and the vibration motor are connected via 24-gauge wires. There are slots for two additional sensors for future implementations. With 2000 mAh, the battery can power the whole unit continuously for more than 2 hours.

4 –  The first IMU sensor is housed into the central electronics hub. In conjunction with IMU #2, the IMU’s captures the angles between the forearm and hand.

5 – The ESP32 is an Arduino-based board that sends all the data wirelessly to the Raspberry Pi via Wi-Fi.

6 – The Secondary Hub contains the second IMU sensor and a Vibration Motor. It is located on the back of the hand and uses Velcro for mounting purposes. It is also created from Thermoplastic Polyurethane to conform to the curvature of the hand

7 – The second IMU sensor is used to calculate the angles of the hand. Using the first IMU as a reference point, it will report these angles to determine when they reach potentially dangerous angles for prolonged periods of time.

8 – The vibration motor provides feedback to the user whenever they approach dangerous levels of pressure and wrist angles.

9 – The 15mm OD Tactilus pressure sensors will interpret pinche forces above 10 N. The Thumb, middle and index finger each have a sensor to accurately map the pressures when grasping objects.

10 – Finger Cots are used to hold the pressure sensors in place. They are made with Nitrile to accommodate for users who are allergic to Latex. It is stretchable and allows for a wide range of finger sizes. 

Calibration:

A Calibration rig is constructed to convert the pressure readings into Newtons. It consists of a load cell connected to the base station Raspberry Pi. The pressure sensors are pressed into the rig to determine the characteristic exponential curve of the pressure sensors. The user places one finger pressure sensor onto the load cell and slowly increases pressure. A python script on the Raspberry Pi will read the response of the load cell to show the force of the finger in Newtons while simultaneously reading the output of the pressure sensor. The finger pressure sensor readings are plotted in the X-axis while the load cell is on the Y-axis. The graph shown is the characteristic calibration curve. An exponential equation is created to convert the unitless finger pressure readings into Newton's of force.