Detecting 13 Wellness Conditions from Voice

One Recording, Thirteen Insights

Traditional mental health screening typically involves structured questionnaires, clinical interviews, or behavioural observations — each focused on a single condition. Happo AI takes a fundamentally different approach: by analysing the acoustic properties of natural speech, it can screen for up to 13 conditions simultaneously from a single audio recording.

This multi-condition capability is not about replacing clinical diagnosis. It's about providing objective, data-driven indicators that complement professional assessment — whether in a sales coaching context where stress and fatigue affect performance, or in medical counselling where early detection of emerging conditions saves lives.

The 13 Conditions

Happo AI's detection system covers a broad spectrum of psychological and physiological conditions, each with distinct acoustic signatures:

• Stress — Elevated muscle tension affects vocal fold vibration, increasing jitter and shifting spectral energy toward higher frequencies.
• Anxiety — Manifests as faster speech rate, higher pitch, and increased breathiness due to shallow breathing patterns.
• Depression — Characterised by reduced pitch range (monotone speech), slower tempo, lower energy, and degraded harmonic structure.
• Panic — Produces sudden, sharp changes in vocal biomarkers including extreme jitter spikes and respiratory irregularities.
• Manic episodes — Higher energy, faster speech rate, wider pitch range, and increased vocal intensity.
• Autism spectrum indicators — Atypical prosodic patterns including unusual intonation contours and rhythm differences.
• ADHD indicators — Speech disfluencies, variable tempo, and attention-related vocal characteristics.
• OCD indicators — Repetitive speech patterns and specific stress-related vocal markers.
• Fatigue — Reduced vocal energy, slower articulation rate, and degraded fine motor control of speech production.
• Burnout — Chronic version of fatigue markers combined with emotional flattening in prosodic features.
• Sleep Apnea — Specific spectral patterns related to airway changes, nasal resonance, and breathing-related vocal quality shifts.
• Emotion states — Real-time classification across 10 emotional categories including neutral, happy, sad, angry, anxious, fearful, disgusted, surprised, frustrated, and calm.
• Mental Exhaustion — A comorbidity indicator that flags when multiple conditions co-occur, recognising that fatigue plus burnout plus OCD indicators together suggest a compound state requiring different intervention.

Acoustic Signatures Vary by Condition

Each condition affects the voice through different physiological mechanisms. Stress primarily impacts the laryngeal muscles, changing vocal fold tension. Depression affects the respiratory drive and neural control of speech, reducing the dynamic range. Anxiety triggers fight-or-flight responses that increase breathing rate and raise the larynx.

Happo AI uses condition-specific feature sets tailored to these mechanisms. The features relevant for detecting depression (pitch range, speaking rate, energy) differ from those used for panic detection (sudden jitter spikes, respiratory irregularities) or sleep apnea (nasal resonance, spectral patterns). This specialisation is what enables simultaneous multi-condition screening without sacrificing accuracy.

Comorbidity Detection

In clinical practice, conditions rarely occur in isolation. A person experiencing burnout is likely also fatigued. Someone with depression may simultaneously show anxiety markers. Happo AI's comorbidity analysis identifies when multiple conditions are present and flags compound states.

The mental exhaustion indicator is particularly important — it recognises that the co-occurrence of fatigue, burnout, and obsessive patterns together represents a distinct clinical picture that is more than the sum of its parts. Comorbidity multipliers adjust the severity assessment when related conditions are detected together.

From Detection to Action

The 13-condition screening output isn't a diagnostic label — it's a structured set of probability scores and severity indicators that professionals can use to guide their assessment. In a sales context, detecting elevated stress and fatigue in a team member triggers a different management response than detecting anxiety. In counselling, tracking how a patient's depression and anxiety scores change across sessions provides objective outcome measurement.

By making these indicators available in real time during live sessions, Happo AI enables immediate awareness rather than retrospective analysis — the counsellor can see when a patient's stress is escalating and adjust their approach in the moment.