Background

As our relationship with domesticated animals, particularly pets, evolve, so does the need for deeper emotional connections and understanding. My interest lies in exploring how emerging technologies such as neurotechnology, biometric sensors, machine learning and artificial intelligence can bridge the communication gap between humans and their pets.

By diving deeper into technologies like neural sensors and AI-driven health monitoring, I see the potential to design a solution to improve human communicative relations: a bridge over the current gap of one-way communication between humans and animals, specifically pets.

Problem

We don't communicate with our pets;
we interact...

More than 8 million species share our planet, but we only understand the language of one. Pets are the closest species to humans; why? because we feel them and they feel us the most. But we don't communicate with them.
Communication includes sending information and receiving back a response, which in any other forms than this, it would be counted as an interaction with no direct understanding.

Thesis question (HMW)

How might we design emerging technologies to enhance human–pet communication and emotional understanding, while prioritizing ethical integration, accessibility, and the overall well-being of both users and companion animals?

Research

Brain and neuroscience

"I definitely think that in terms of recording from the brain, your best option would be a portable EEG, unless you want an implant.
The way the brain is organized, the regions of the brain, and even the lobes are pretty identical between species, especially when you're talking about mammals like mice, rats, cats, dogs, and humans. So, the size would change, but not the actual technology itself, and the concept is always going to remain the same if you go with EEG, you're going to have the external electrodes attached through some sort of helmet."
‍
Ahmad Israwi

Neuroscience Researcher, Doctoral Candidate in Neuroscience at the University of Toronto

Technologies and materials

After attending the "Computational Neuroscience" event at kite UHN, by Dr. Brokoslaw Laschowski, I discovered the potentials at the intersection of  machine learning and neuroscience

"In our research lab, we develop new computational and machine learning models to decode neural signals from the brain which encode information about procesies such as cognition and motor intent."
‍
Dr. Brokoslaw Laschowski

Computational Neuroscientist, Research Scientist and Principal Investigator at the Toronto Rehabilitation Institute, Assistant Professor at the University of Toronto

Stakeholders

Secondary Research and information maps

Perceptual map and product value

Key findings

Solution

Pave the path of communication and bonding

Pave is the communication bond between human and animals using Neurotechnology, through an app and a physical wearable for dogs and cats.
By leveraging non-invasive EEG technology, this system scans animal's brain and displays the translated brainwaves data in the app for the owner to monitor their pets' emotional and cognitive states. Using Neurostimulation capabilities (tDCS) users can send training cues, direct monitored communication cues, or therapeutic signals back to the pet’s brain as well.

Design process

Phase 1: Ideation to Low-fidelity

The process started with +20 early sketches and ideations on how the wearable could look like.
Then by choosing two raw ideas, I started creating low-fidelity prototypes with magnets and papers and tested on small dog sculpture.
Later I started generating refined versions of the drawings using AI (MidJourney and Dali) to have an easier decision making and visualization of the concepts.

Meanwhile, I also started making flow maps of the app, including sign up to create a user journey while collecting the determined user data.

Phase 2: Mid-fidelity

The physical prototype continued after 3D printing a real-life dog and a cat model, while researching the exact measurements and materials.

With taking inspiration from products like VR headsets and dog goggles, I came up with the idea of a cap with attachable parts that are stretchy to fit the animal's skull.

The parts include a piece surrounding the neck, a piece that covers the top of the head, and a piece between the ears that connects the top piece to the neck piece. This was later simplified into two pieces as I decided to create two sizes of the product.

Phase 3: High-fidelity

neurocap™ (wearable)

The final wearable called Neurocap™ includes two sizes of small (cats and smaller dog breeds) and large. It's made out of polyester fabric on the sides, soft woven elastic and 3D printed PLA buckles for resizing and adjusting the helmet. There's stretchy cotton used for the top piece to adjust and breathable for the animal skin, and includes 4 aluminium grommets to attach the sensors to.

The sensors have two parts which includes a top piece that is printed in PLA Silk+ and TPU on the tip (electrode) to easily click into the grommets.

Pave mobile app

Pave mobile app is a companion tool that visualizes the emotional and health data of the user's pet in real time using brainwave and muscle activity analysis. Paired with the wearable device, it offers live insights, behaviour trends, training feedback, and communication cues.

Packagine

Section is under work.