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Real-time visuals for stress and anxiety that respond as you breathe

Hacker News

Real-time visuals for stress and anxiety that respond as you breathe

I’m an NHS doctor and the founder of Pi-A ( https://www.pi-a.io ) which developed Lungy ( https://www.lungy.app ). Lungy is an iOS app that responds to breathing and was designed to make breathing exercises more engaging and beneficial to do. It hopefully has many aspects of interest to the HN community – real-time fluid, cloth and soft body sims running on the phone’s GPU. My background is as a junior surgical trainee and I started building Lungy in 2020 during the first COVID lockdown in London. During COVID, there were huge numbers of patients coming off ventilators and they are often given breathing exercises on a worksheet and disposable plastic devices called incentive spirometers to encourage deep breathing. This is intended to prevent chest infections and strengthen breathing muscles that have weakened. I noticed often the incentive spirometer would sit by the bedside, whilst the patient would be on their phone – this was the spark that lead to Lungy! I had never coded or developed an app before but had a background in 3D design and Houdini which uses an expression language called VEX. I started to learn Swift and Metal in the evenings during lockdown and eventually, I had a good enough understanding to build a working prototype. After the first year, I won a couple of small government grants to develop Lungy further and build a small team. I managed to find some talented developers, and over 5 months (Nov 21 – Mar 22) we built the basis for Lungy as it is today. The visuals are mostly built using Metal, with one or two using SpriteKit. There are 20 to choose from, including boids, cloth sims, fluid sims, a hacky DLA implementation, rigid body + soft body sims. The visuals change each day in the free version, and are fully unlocked in the premium version. The audio uses AudioKit with a polyphonic synth and a sequencer plays generated notes from a chosen scale (you can mess around with the sequencer and synth in Settings/Create Music!). There are obviously lots of breathing and meditation apps out there, I wanted Lungy to be different. Rather than closing your eyes and zoning out, Lungy is about tuning into your surroundings and noticing the world around you, so all the visuals are nature inspired or have some reference to the physical world. I didn’t like that apps like Calm and Headspace require large downloads and/or a wifi connection, so Lungy’s download size is very small (<50MB), with no geometry, video or audio files. Lungy is initially a wellness app, but I’d like to develop a medical device version for patients with breathing problems such as asthma, chronic obstructive pulmonary disease (COPD) & long COVID. I’m collaborating with a prof at UCL to try and complete a feasibility study next year. Thanks for reading - would love to hear feedback!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios, including · Missing: supports, reddit linkedin, podcasting
94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, visual, physical · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps, video · Missing: mobile apps, personal, entrepreneurs
65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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