4.9
11,139 条评分
★★★★★
2026年5月13日
2022年11月15日
更新内容
v6.13.0We've enhanced Innertune and eliminated bugs, making your experience even more enjoyable. Enjoying Innertune? Share your thoughts with a review! Your feedback is invaluable, and it helps others find our app too!
应用信息
- 开发者
- Innertune Media Inc.
- 分类
- Health & Fitness
- 价格
- 免费
- 版本
- 6.13.0
- App ID
- 6443625379
简介
Stop the negative thought spiral. Innertune uses repetition principles from neuroscience research to help shift your mindset. Press play. Let it work while you sleep, work, or relax. Designed to help with: • Anxiety and racing thoughts • Sleep and restless nights • Self-doubt and confidence • Breaking negative thought patterns How it works: Builds a personalized playlist for your exact situation. Choose your voice. Record in your own (the one your brain trusts most) or pick from 10 professional voices. Match your mood with beats for focus, relaxation, or sleep. Press play. Loop it. Let repetition do the work. What's inside: • Unlimited listening time • Night mode for sleep • Daily reminders Premium unlocks: • AI-personalized playlists • 10 voices (including ASMR) • 100+ binaural, sleep, motivation, relaxation, and focus beats • Record in your own voice • 22,000 affirmations, 550+ playlists • Offline downloads • Zero ads Real results from 1.1M+ users. - "This app changed my life. I'm finally sleeping through the night." - "Recording in my own voice is a game changer. Nothing else worked." - "I feel confident for the first time in years." Start free. Upgrade anytime. Subscriptions auto-renew unless canceled 24 hours before renewal. Your subscription will be billed to your Apple Account. Manage in Apple Account settings. If you need assistance or have a question, you can contact our friendly team at: support@innertune.com With Love, The Innertune Team. Your privacy matters to us. Read our Privacy Policy and Terms of Use: https://innertune.com/terms-and-conditions https://innertune.com/privacy-policy
下载量预测
预估总下载量
17K
低 / 月
24K
预估 / 月
37K
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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