CastMinder - The Cast and Splint Monitoring System

The CastMinder system can detect complications in orthopedic casts and splints while healing patients faster and with less pain.

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CastMinder is a smart Bluetooth-enabled sensor system designed to predict complications in orthopedic casts and splints before they arise. The CastMinder system consists of a few key components.

The primary devices in the CastMinder system are tiny sensor nodes embedded inside of a cast or splint. These sensor nodes continuously collect data and dump it via Bluetooth to an iOS application which serves as the brains of the entire network. These small nodes are equipped with a variety of sensors, such as a pressure sensor to detect compartment syndrome, a temperature sensor to detect patient fevers, and a moisture sensor to detect skin bleeding and irritation. Other devices worn on the cast use electrical stimulation to lessen patient pain and stimulate bone growth. The entire system is controlled by the CastMinder iOS app, which can both analyze data to future conditions and alert physicians, nurses, patients, and more to potentially harmful changes in the status of the cast.

My name is Alex Wulff. I’m currently 17 years old. Below is the long-winded answer for the question "what exactly is CastMinder?"

You can view more information and see more photos on the CastMinder project site. You can also view the poster.

In a nutshell, CastMinder is a system that can monitor conditions inside orthopedic casts and splints to detect conditions associated with the onset of complications. These include skin infection, skin irritation, bleeding, and something called compartment syndrome, where an excess of pressure can lead to circulation loss in the casted limb. Additionally, I’ve incorporated devices into this system that can increase the rate at which new bone is formed, and decrease patient pain during the healing process. Embedded under the cast are small sensors, which collect data about conditions inside the cast or splint. These devices then send data to an iPhone application that I’ve spent hundreds of hours (way too much time) working on. This application can collect and analyze this data and predict the onset of harmful conditions before they arise inside the cast. The whole system is patent-pending!

The iOS Application with a tester’s cast

At the heart of many of the devices in this system is Punch Through Design’s LightBlue Bean. The Bean is literally perfect for my project because it integrates Bluetooth, ultra-low-power operation, and a variety of onboard sensors into one concise package. The devices actually embedded inside the cast utilize a variety of different sensors to determine environmental conditions inside the patient’s cast. These sensors include a force-sensing resistor, homemade moisture sensors, and the Bean’s onboard motion and temperature sensors. The programming for these nodes is actually quite simple — all they do wake up at certain intervals, collect data from the various sensors, package it into one long string, send it via virtual serial to my iOS app for processing, and go back to sleep to save battery.

A sensor node in my 3d-printed case

The iOS app is where things get a bit more complicated. Every time the iOS application receives data, it needs to check to make sure this data falls within defined parameters, but then it needs to add this data to a stack for analysis. I wrote an algorithm that analyzes thousands of sensor logs from this stack to determine not just that something could be immediately wrong inside of a user’s cast, but when complications may be at risk of developing. If so, the application also needs to alert the proper parties that something is wrong, and convey this to the patient. I’ve paired the app’s overhead down from using a quite hefty 50% of the device’s CPU (you could use it as a hand warmer) to a much more manageable 3% on every incoming serial message. The app also has to run in the background to continuously receive sensor data from the Beans, so I had to work really hard to get the energy impact low as well. While all these complex processes are happening, the app needs to display this data in a nice format to the user upon request, without any lag.

The CastMinder iOS Dashboard

The iOS application also has the important task of controlling what I call the “active healing” portion of my project, which involves increasing the rate at which new bone is formed, and decreasing patient pain. I accomplish this through a combination of two separate devices — a transcutaneous electrical nerve stimulation (TENS) device and a bone growth stimulator. Both of these devices are prescribed outside of orthopedic casts and use electrical stimulation; however, this is the first time that someone has actually combined these two devices into one, and integrated them into a cast. The active healing unit is powered by, you guessed it, a LightBlue Bean. The iOS app allows the user to configure and turn on/off either system. It then sends this data to the Bean via virtual serial to interpret it and adjust the electrical output accordingly.

The CastMinder TENS controller... Read more »

Gerber files for the CastMinder RF24 Reciever

Zip Archive - 60.92 kB - 10/10/2016 at 12:44


Gerber files for the CastMinder RF24 Wireless sensor node

Zip Archive - 62.42 kB - 10/10/2016 at 12:42



3D model of the CastMinder Sensor Node 3D-printed Case

step - 1.52 MB - 10/10/2016 at 00:50



Fusion archive of the CastMinder Sensor Node 3D-printed Case

f3z - 1.13 MB - 10/10/2016 at 00:50


CastMinder Active Healing.step

3D model of the 3D-printed active healing unit device.

step - 1.05 MB - 10/10/2016 at 00:50


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  • Possible Use Cases for CastMinder

    Alex10/10/2016 at 02:15 0 comments

    Portions of CastMinder are more useful in some cases than in others. A great illustration of this is a buildup of pressure. A patient who has broken her arm but is otherwise healthy and walking around would be immediately able to sense when the pressure in her cast is getting too high, as she would feel pain. However, a patient who is unconscious in a hospital would not be able to communicate such problems. Thus, having a sensor inside of such a patient's cast can prove immensely useful for physicians.

    A moisture sensor is useful for most patients. Oftentimes it can be quite difficult to detect the presence of moisture inside of a cast.

    The active healing unit is obviously useful for any patient, as an increase in bone formation and a decrease in pain would be beneficial to anyone.

  • CastMinder GitHub Repositories

    Alex10/10/2016 at 02:07 0 comments

    I've only recently posted the CastMinder code in full on GitHub. This is split between two repositories, the repository for the Arduino code and the repository for the iOS application. Most of the code for the Arduino portion is quite simple - after all, all these nodes are doing is collecting data, sending it, and going to sleep. The iOS app is where things start to get a bit more complicated.

    There's thousands of lines of code that I'm working hard to document in the CastMinder iOS app. There's also a lot of cleaning up that I need to do before I'm really proud of the code I produced. Thus, what I have posted on GitHub is by no means a finished product, but it should work. If you have any suggestions please do not hesitate to contact me at info[at]

  • New CastMinder Project Video

    Alex10/10/2016 at 02:00 0 comments

    I recently produced a video that shows some of the components of the CastMinder system in action. If you're curious about what the app actually looks like in real life, you can check out the video below.

  • Building the Active Healing Unit

    Alex10/10/2016 at 01:55 0 comments

    Soon I'll have build instructions and a formal component list available for the active healing unit. Here's a preliminary and general list:

    • The first component is a LigthBlue Bean. This allows the device to be controlled from the CastMinder app via Bluetooth
    • A 9v battery is used to power the whole system
    • A step-down voltage converter is used to provide the Bean with a nice steady 3v (no CR2032 needed!)
    • A step-up voltage converter is used to provide power to the electrodes.
    • Rather than controlling the input to the step-up converter, I'm using a power MOSFET to control the output. This way I don't need to worry about charging and draining the capacitors in the step-up converter which can mess with the frequency of the output

  • TENS and Active Healing

    Alex10/09/2016 at 20:34 0 comments

    The Transcutaneous Electrical Nerve Stimulation (TENS) unit is an integral part of the CastMinder Active Healing system. Regular TENS units work by providing relatively high voltage (approx. 50v) pulses to the skin through electrodes. These pulses are generally in the 1-10hz range, or slow enough that a human can differentiate between the different pulses.

    I'm currently working on getting the correct pulse width dialed in. This will involve lots of trial and error, as It'll just be a matter of seeing what lessens pain the most. The pulse width and timing is also somewhat subjective, as different people respond in different ways.

    These pulses stimulate blood flow around the affected area, lessening patient pain. My Active Healing unit combines a TENS unit with a Bone Growth Stimulator, which I'll talk about in another log.

  • AI and Advanced Learning in CastMinder

    Alex10/02/2016 at 12:32 0 comments

    One of both the benefits and drawbacks of the CastMinder system is its tendency to produce data. A lot of data. One sensor log per second from up to fifteen sensors means thousands of sensor logs an hour. One of the questions I was faced with while designing CastMinder was how can I use this data to help detect complications?

    I've developed a few solutions. Lately, I have been experimenting with a great GitHub library called Swift AI that makes it easy to add Machine Learning to iOS apps. I can use the GPU-accelerated algorithm to parse thousands and thousands of data points, then develop correlations between them to predict future cast conditions.

  • About CastMinder Testing

    Alex08/26/2016 at 23:19 0 comments

    Currently, CastMinder has been tested for over 210 hours. This is a lot of testing data, but these tests were only performed on healthy testers--testers with no broken or fractured limbs. After the entire system is developed further, we'll begin testing CastMinder on individuals with real broken bob

  • Current State of Battery Life

    Alex08/25/2016 at 19:34 0 comments

    The CastMinder Bluetooth system currently relies on the Lightblue Bean as the primary Bluetooth chip and microcontroller. The Bean is great at saving battery, but it can only go so far on a coin cell. A CR2032 lasts about a month and a half with optimized Bluetooth settings. I could decrease the packet transmission time to get it to last a bit longer, but that would be at the expense of real-time data analytics. An easy solution is to include a bigger battery. I've gotten my device to last upwards of 3 months on bigger coin cells.

    My RF24 system is much more power efficient as it uses a lower-power radio to communicate, and doesn't advertise as frequently. This system can last almost half a year on a single CR2032 battery.

  • Intellectual Property Update

    Alex08/25/2016 at 16:14 1 comment

    CastMinder is currently patent-pending, a distinction afforded to it when I registered and filed a provisional patent for the project. I'm currently in talks with lawyers to get full patent protection.

  • CastMinder Systems

    Alex08/23/2016 at 20:09 0 comments

    Recently I've been developing two separate CastMinder systems. The "smart" system is the one I describe in the most detail. It consists of Bluetooth sensor nodes and an iOS application. However, I've also been working on a "dumb" system, which uses RF24 chips to talk to a receiver. The dumb system does have certain advantages, such as the fact that the battery lasts much longer, and it costs almost 4 times less than the Bluetooth system, not even including the cost of a phone.

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