How it works:
01 Detect
Heart rate and HRV from wearables, microfacial expression and vocal tone via camera.
02 Intervene
When a spike is detected, the app steps in immediately with grounding tools, journaling prompts, and personal resources the user and their therapist has set up in advance.
03 Report
Before the weekly therapy session, a structured summary of the patient's week is ready to share with the therapist - spikes, patterns, trends, and the patient's own words.
How it works:
heart rate and HRV from wearables, microfacial expression and vocal tone via camera
when a spike is detected, the app steps in immediately with grounding tools, journaling prompts, and personal resources the user and their therapist has set up in advance.
before the weekly therapy session, a structured summary of the patient's week is ready to share with the therapist - spikes, patterns, trends, and the patient's own words.
Early Exploration
Before committing to a visual direction, we used Figma Make to rapidly prototype an early version of the app. It let us test the core flows - onboarding, calibration, the home screen, daily review - without spending time on polish. The result was a functional, explorable prototype in a completely different visual language than where we ended up.
Seeing it in motion made it clear what was working conceptually and what needed rethinking.
User Feedback
Competitor Analysis
The market already has players - Blueprint, Greenspace, Neuroflow - but they all share the same blind spot: high patient effort, no passive data capture, and pricing structures that make broad adoption difficult.
Lucid's differentiator is that it doesn't ask anything of the user at the moment. The data is already there - collected passively - and surfaced only when it's useful.
Lucid
UX/UI
2026
The Problem:
Therapy happens once a week. Life doesn't.
There are 167 hours between therapy sessions. That's 167 hours of emotional data - stress spikes, difficult moments, quiet patterns - that go completely undocumented. Patients have no way to make sense of it or share it with the person who could actually help, and therapists walk into every session essentially blind, relying on whatever their patient happens to remember.
The Solution:
167 hours of missing data. Found.
Lucid sits passively in the background - using your smartwatch and phone to monitor biometric signals in real time. When a stress spike is detected, it prompts the user to add context: what were you doing, what did you feel, what might have caused it. At the end of the day and week, everything is compiled into a clear summary that both the patient and therapist can review together.
Key Features
01
Stress spike detection
When the app detects a spike, it opens a prompt - not a survey, not a clinical form. Just: "I noticed a spike. Did you feel it? Let's break it down so you don't carry it alone."
The user can type what happened or record a short video note. The app then surfaces personal grounding tools - a song that the app learned usually calms him, a picture that his therapist set for him, a mantra, or a contact to call.
The tools are either ones that the therapist or the patient set in advance or ones that the app detected as helping over time.
02
Daily Summary
At the end of the day, Lucid puts together a clear picture: when the spikes happened, how intense they were, what context the user added, and what helped.
03
Weekly Summary
The app knows when therapy is coming. It sends a nudge ahead of time: "Let's prepare for the session with Rachel, and look at your week together." It turns the time before therapy into something more intentional than just showing up.
The summary contains trends, peak days, improvements, and pattern insights. The patient can send it directly to their therapist with one tap.
How it works:
01
Detect
heart rate and HRV from wearables, microfacial expression and vocal tone via camera
02
Intervene
when a spike is detected, the app steps in immediately with grounding tools, journaling prompts, and personal resources the user and their therapist has set up in advance.
03
Report
before the weekly therapy session, a structured summary of the patient's week is ready to share with the therapist - spikes, patterns, trends, and the patient's own words.
Personas
Two sides of the same gap
Yoav
34, Project Manager, Tel Aviv
Yoav has been in therapy for eight months, seeing his therapist every Wednesday. His weeks are dense - deadlines, noise, a lot of pressure he doesn't always have words for. He wants therapy to actually work, but when he sits down and gets asked "how was your week?" he genuinely doesn't know where to start. The moments have already blurred. He leaves sessions feeling like he only scratched the surface.
Rachel
47, Licensed Therapist, Tel Aviv Rachel sees 25 patients a week. She's experienced, she's attentive, and she works hard - but she walks into every session essentially blind. She knows what her patients choose to share, filtered through memory and mood. She's been looking for a way to get a clearer picture of her patients' weeks, not because she doesn't trust them, but because she knows how much gets lost in the gap.
The Process
Problem mapping
We started with a topic - Resilience. Mental health, crisis, trauma - we had a lot of directions we thought might be worth exploring. Early sessions pulled us toward PTSD, panic attacks, and emergency intervention. The whiteboards filled up fast.
But the more we talked to people - patients, therapists, clinicians - we realized we were solving for the wrong moment.
It took most of the process to get there, but we eventually landed on the "HMW" question that made everything click:
"How might we make what happens between therapy sessions visible and understandable to both patients and their therapists?"
Research & Ideation
To find our direction, we talked to people - patients dealing with post-traumatic stress and therapists who work with them. We ran brainstorming sessions and worked with mentors from Wix in two dedicated workshops, where we focused on building out the user story and figuring out how we actually imagined the product working in practice. Those sessions helped us move from a vague direction to something we could sketch and test.
Clinical Validation with Mount Sinai
Throughout the process, we worked closely with Dr. Craig Katz, a Senior Psychiatrist at Mount Sinai Hospital in New York. He reviewed our research, pushed back on our assumptions, and signed off on the language we used inside the app, which, in mental health matters more than it might seem. He also pointed us toward current research on facial recognition as an emotional indicator, which ended up becoming a core part of how Lucid detects stress.
I flew to New York to meet and personally present our ideas. He liked it, and then he got specific. He told us that in therapeutic contexts, language is everything - patients respond to questions, not statements. That note changed how we wrote every prompt in the app.
He also introduced us to current research on reading facial expressions and vocal patterns as emotional indicators. It opened up a direction we hadn't considered, and it ended up becoming one of the most central features in the product.
Lucid is a biometric monitoring app that lives between therapy sessions. It was developed as part of the Design Thinking course at Tel Aviv University, in a cross-disciplinary team of designers, engineers, and MBA students, and won 'Best Project'.
We worked closely with Dr. Craig Katz, a world-renowned psychiatrist from Mount Sinai, who validated the process throughout and guided our clinical framing, research direction, and the language we implemented throughout the product.
The problem we set out to solve is: therapists ask "how was your week?" and patients say "I guess okay". Not because nothing happened - but because memory fails, and the 167 hours between sessions go entirely undocumented. 'Lucid' changes that - passively collecting biometric data, helping users make sense of their own patterns, and giving therapists a real picture of their patients' week before they even walk through the door.