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Transform cardio machines into arcade games

Hacker News

Transform cardio machines into arcade games

My friend and I have built a mobile video game that can be played on an exercise bike/elliptical. Using the camera we track micro-movements of the body and detect the speed of motion, and use head tracking for steering. Currently the game is in prototype mode, and consists of trying to pass obstacles, collecting orbs and destroying enemies. Here is a link to a video of the playthrough: https://vimeo.com/189210575 If you would like to try the game out, you can register on our website: pelatra.com. You will get access to this specific prototype and all upcoming versions of the game. Any feedback, questions or concerns would be very useful so please let us know what you think.

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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, using · Missing: agents, macos, agent
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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