# Title Team Members TA Documents Sponsor
45 Continuous Arteriovenous Fistula (AVF) Monitoring Device [PITCHED PROJECT]
Aryan Parikh
Rishab Rao Veldur
Satyansh Yeluri
Surya Vasanth design_document1.pdf
# Continuous Arteriovenous Fistula (AVF) Monitoring Device

Team Members:
- Aryan Parikh (aparik31)
- Rishab Rao (rveldur2)
- Satyansh Yeluri (syeluri2)

# Problem

Arteriovenous Fistulas/Grafts (AVFs/AVGs) are crucial to patients with end-stage kidney disease. They allow for hemodialysis, which has significant mortality and quality of life benefits in younger patients. Between 2000 and 2020, the prevalent count of individuals receiving HD nearly doubled to $480,516. In older patients, it’s often considered a lifeline. However, AVFs are known to “go down”. They are susceptible to stenosis, and thrombosis, and enlargement over time, leading to high-output cardiac failure. Currently there is no format for continuous monitoring of these grafts, and when they thrombose in the acute setting, often go undetected for days, if not weeks. The cost range to create an AV fistula is also between $3,401-$5,189. Several studies have pointed out that early graft intervention can improve the salvage of these fistulas, prolonging their use and minimizing the number of additional surgeries required. Finally, studies have found that if grafts are not intervened within 7 days, there are significant long term mortality risks and poor patient outcomes.

The basic tenet for vascular access monitoring and surveillance is that stenosis develop over variable intervals in the great majority of vascular accesses and, if detected and corrected, under dialysis can be minimized or avoided (dialysis dose protection) and the rate of thrombosis can be reduced.

Problem Statement: Graft stenosis and thrombosis are the leading causes of loss of vascular access patency, with delay in treatment leading to loss of vascular access and increased mortality rates and decreased quality of life in patients with end-stage renal disease.

# Solution

AVFs are often embedded in the arm, where the radial artery and adjacent veins are involved in their creation. What clinicians use to determine fistula viability is palpation, where the palpable trill (or vibration) of the graft can be felt. In the context of vascular access for hemodialysis, a trill is often associated with the feeling of blood flow or the movement of blood through the graft. A strong, palpable trill suggests good blood flow through the access site, indicating that the fistula is functioning well.

The idea is to develop a device that can be attached as a patch adjacent to the fistula to sample this venous trill using auditory input and machine learning to gauge deviations from an initial baseline. The device would be placed initially and cross-referenced with the current gold standard of duplex ultrasound to establish a baseline. As the device lives with the patient, it will learn progressive changes in venous hum pattern (stenosis) that can provide information to clinicians on optimal follow-up. Otherwise, if it detects the absence of a hum (thrombosis) it will immediately alert the patient and provider for attention. Pitch should correspond with an increase in percentage of stenosis and be interpreted as more frequent oscillations in a pressure waveform over time.

# Solution Components

## Microphone

This subsystem would take in sound input from a small microphone to capture a signal underneath the skin and feed into a microprocessor input.

TDK InvenSense T4076 & T4078 MEMS Microphones

## Microprocessor Unit

We will use an Attiny85 and supporting components on our PCB. We will have to add a micro usb programmer for the Attiny85 and then add bluetooth capabilities on top of that. The microcontroller will receive input from the Microphone Module which captures acoustic signals related to venous hum patterns. These signals are essentially sound waves produced by blood flow in veins. We will use an algorithm on the acquired data to help analyze the different frequency components present in the venous hum patterns. Then the microcontroller can analyze the frequency spectrum of the venous hum patterns. The microcontroller can then help us compare the identified patterns with predefined patterns associated with normal and abnormal venous conditions. Based on the comparison, the system can detect differences in the venous hum patterns. Depending on the detected differences, the microcontroller will generate an alert if needed.

## Power Subsystem

It will be a 5 V lithium ion battery. We will have to step down the voltage to 3.3 V. We have no need for battery recharging. We will also have supporting components for the battery.

# Criterion For Success

- Transmit audio to app
- Accuracy: Device is able to distinguish changes in fistula stenosis
- Achieve real time data transmission


Srinija Kakumanu, Justin Naal, Danny Rymut

Featured Project

**Problem:** When working out at home, without a trainer, it’s hard to maintain good form. Working out without good form over time can lead to injury and strain.

**Solution:** A mat to use during at-home workouts that will give feedback on your form while you're performing a variety of bodyweight exercises (multiple pushup variations, squats, lunges,) by analyzing pressure distributions and placement.

**Solution Components:**

**Subsystem 1: Mat**

- This will be built using Velostat.

- The mat will receive pressure inputs from the user.

- Velostat is able to measure pressure because it is a piezoresistive material and the more it is compressed the lower the resistance becomes. By tracking pressure distribution it will be able to analyze certain aspects of the form and provide feedback.

- Additionally, it can assist in tracking reps for certain exercises.

- The mat would also use an ultrasonic range sensor. This would be used to track reps for exercises, such as pushups and squats, where the pressure placement on the mat may not change making it difficult for the pressure sensors to track.

- The mat will not be big enough to put both feet and hands on it. Instead when you are doing pushups you would just be putting your hands on it

**Subsystem 2: Power**

- Use a portable battery back to power the mat and data transmitter subsystems.

**Subsystem 3: Data transmitter**

- Information collected from the pressure sensors in the mat will be sent to the mobile app via Bluetooth. The data will be sent to the user’s phone so that we can help the user see if the exercise is being performed safely and correctly.

**Subsystem 4: Mobile App**

- When the user first gets the mat they will be asked to perform all the supported exercises and put it their height and weight in order to calibrate the mat.

- This is where the user would build their circuit of exercises and see feedback on their performance.

- How pressure will indicate good/bad form: in the case of squats, there would be two nonzero pressure readings and if the readings are not identical then we know the user is putting too much weight on one side. This indicates bad form. We will use similar comparisons for other moves

- The most important functions of this subsystem are to store the calibration data, give the user the ability to look at their performances, build out exercise circuits and set/get reminders to work out

**Criterion for Success**

- User Interface is clear and easy to use.

- Be able to accurately and consistently track the repetitions of each exercise.

- Sensors provide data that is detailed/accurate enough to create beneficial feedback for the user


- Designing a circuit using velostat will be challenging because there are limited resources available that provide instruction on how to use it.

- We must also design a custom PCB that is able to store the sensor readings and transmit the data to the phone.