How does W3LL provide insights without user input?

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W3LL Leverages Passive Behavioural Signals for Insight Generation

The W3LL application provides insights into a user's well-being by analysing passive behavioural signals, eschewing traditional methods like form-filling or mood tracking. It focuses on subtle shifts in everyday patterns, such as movement and sleep, to establish a personalised baseline for each user over an initial period of five to fourteen days. This approach allows the app to offer a daily assessment of calm, focus, and energy levels, alongside predictions of behaviour and tailored recommendations.
Behavioural Rhythm Engine™ Drives Insight Analysis

At the core of W3LL's functionality is the Behavioural Rhythm Engine™ (BRE). This proprietary engine is designed to translate observed behavioural patterns into actionable insights. Rather than relying on direct user input regarding their feelings, the BRE interprets data derived from a user's daily activities, effectively bridging the gap between how an individual feels and their actual capacity or performance.
Analysis of Everyday Patterns Forms Baseline

W3LL's methodology is built upon tracking and analysing changes in a user's everyday routines. Specifically, it draws upon data related to movement and sleep patterns. By observing these fundamental aspects of daily life, the app constructs a unique rhythm for each individual. This personalised baseline is crucial, as W3LL compares each subsequent day's activity against this established norm, rather than against a generic standard of well-being.
Focus on Early Detection of Subtle Shifts

The app's design prioritises the early detection of gradual shifts in an individual's state of mind and energy. It aims to identify these changes before they escalate into significant problems or impact an individual's ability to manage their responsibilities, such as academic or work-related tasks. This proactive stance is supported by research published in Applied Sciences, which underpins W3LL's translation of validated behavioural science into a practical daily tool.

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How does W3LL provide insights without user input?

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