A mouse for shaky hands

Hacker News

Hand tremors from Parkinson's disease and Essential Tremor can make using a computer mouse nearly impossible. The cursor not only flies everywhere but accidental clicks also result in unexpected actions being taken. This of course is extremely frustrating. After my grandfather was diagnosed with Parkinson's in 2003-2004 I saw this first hand and consequently set about solving the problem in software. SteadyMouse was born. The software contains both an anti-tremor motion rejection algorithm to keep things stable, and an accidental click blocking mechanism to only let through intended clicks. The last two years were spent on a massive upgrade for a commercial version (in addition to the original free version). Here's a gif of the filtering in action: https://twitter.com/steadymouse/status/890794753637326848 The main site is here: https://www.steadymouse.com/

Visit product View on Hacker NewsAug 2, 2017

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5points

1comments

Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: cursor, computer, using · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% 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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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