Tech & Science

How Kalmoa works

Technology in plain language, and the science it stands on.

Kalmoa reads the signals being sent by your actual body – not a questionnaire – to uncover how you are doing, mentally and emotionally. Just five minutes wearing a comfortable headset is enough for the Kalmoa app to generate a clear, readable picture of your mental wellbeing. Let us walk you through how that works, and then the established science it is built on.

Part 1 · How the technology works

Most wellbeing tools ask you how you feel and trust your answer. The problem is that we are not always reliable narrators of our own state: we talk ourselves up on a bad day, or brush off strain we have gotten used to. Kalmoa takes a different route. It measures the body directly, to generate more reliable results that are not subject to personality differences or mood fluctuations.

Under the hood, Kalmoa works in three steps

1
Scan

During the scan, the Psyray scan app will show you carefully selected images while the headset plays a structured sound sequence and measures how your brain-body system responds.

2
Compare

Your responses are compared to an extensive reference-model database to identify key patterns.

3
Report

These findings are translated into a clear, personalized Deep Report and WellBeing Index, which are then available in the app.

The scan: gently asking your body a question

Your brain is in constant, two-way conversation with your body: it is always quietly reading signals from your heart, lungs, gut, and muscles. Most of that traffic happens on a subconscious level, yet it shapes whether you feel calm or on edge, energetic or drained. Kalmoa listens in on that conversation. During the scan, the headset plays a carefully structured sequence of sounds while you view specific images, selected to trigger brain responses, in the app. Think of each sound and image as a gentle question to the brain-body system. Inside the headset, a pleasant reference white-noise field is generated; as your system responds to the sounds and images, it subtly changes that field, and the pattern of those changes is the data your scan is generating.

This is not a medical scan. Kalmoa does not perform an ECG, EEG, or MRI, and the scan does not measure anything anatomical. It is a comfortable, non-invasive experience: no needles, no lengthy testing. It simply observes how your system reacts to a set structure of prompts.

The comparison engine: one measurement means little; the pattern means a lot

The scan data is sent to the Kalmoa cloud engine. On its own, a single reading says almost nothing. Meaning comes from comparison. The engine is powered by a reference model built on more than 40,000 reference scans – and, rather than reading any single scan result in isolation, it evaluates the overall pattern: where it deviates from the norm, which deviations actually matter, and how the pieces fit together. Our system compares your personal patterns to thousands of others, and using pattern recognition to pinpoint similar pattern complexes. These similarities are the basis of the content for the Deep Report and WBI.

The report: your Well-Being Index, in plain language

These findings are organized into an easy-to-read report you can actually understand. It’s more than a single score – it’s an entire Wellbeing Index. You can explore your profile across seven dimensions of psychological functioning, for an at-a-glance picture of where you stand. Going deeper, your report expands that profile across three layers:

The current picture – how you are functioning right now. In plain words, so both your strengths and your points of strain become visible.

Underlying themes and patterns – the recurring tensions or ways of coping that help explain how you arrived where you are, and what is keeping you there.

Directions for support – clear areas to focus on, plucked from your personal pattern. Meant as a starting point for reflection, not a fixed prescription.

A modern AI LLM is used in this last layer only, to turn the findings into clear, well-written text adapted to you. It is a communication tool, not the science: the substance always comes from the measurement and the comparison with the reference-model database.
 

A simple way to picture it

Think of a music-recognition app, like Shazam.

It does not understand a song by analyzing one note. It captures a pattern, the full melody, and compares that pattern against a huge database, returning the most likely match. Kalmoa works at a far more complex level, but the logic is the same: capture a structured response pattern, compare it to a large database of other references, and translate the best-matching patterns into meaningful language. And, just as Shazam gets sharper with a bigger, cleaner music library, Kalmoa gets sharper as its reference base grows.

Let’s make one thing clear, though: Kalmoa is a tool to support you in your own decision making. It is not a diagnosis. It does not read your thoughts or replace professional judgment. It gives you, and any professional you choose to involve, a fast and structured view of your inner dynamics: a better starting point for a conversation, but not the final word.
 

Part 2 · The science it stands on

Kalmoa does not rest on a single new or untested idea. It stands on decades of findings and developments across five independent fields of science, supported by peer-reviewed research. The interesting part is the convergence between these fields: many different research groups, using very different methods, keep pointing the same way.

The science of Kalmoa is supported by five pillars. In plain terms with real-life examples:

1. Interoception: Your body is always talking.

Interoception is the brain's sense of your body's internal state. It’s the inward-facing counterpart to seeing and hearing. It reports on your heartbeat, breath, gut, muscle tension, and more – systems that usually operate beneath conscious awareness, yet color everything you feel. Over the past two decades, researchers have tied this sense directly to emotion: how accurately someone can feel their own heartbeat, without checking their pulse, relates to how vividly they experience and regulate emotion 1. Another recent review concludes that emotional experience is intimately tied to interoception 2, and this internal signaling is measurably disturbed in cases of anxiety, depression, and post-traumatic stress – times when the brain-body conversation becomes noisy or muted 3.

A real-life example: You walk into a room and feel that something is off before you can put it into words. That is interoception at work; your body registered the tension before your conscious mind caught up.

2. The predictive brain: Probing beats watching.

The old picture of the brain was as a video camera, passively recording the world. Modern neuroscience counters: the brain is a prediction machine, constantly guessing what is about to happen inside and outside the body. This forward-looking regulation, the way our brains help us adjust in advance, is called allostasis. When reality does not match the prediction, the brain learns from that mismatch 4. Emotions, in this view, are the brain's best interpretation of the body's state in a given moment, assembled from bodily signals plus memory and expectation 5. The practical lesson: if the brain and body form an active, self-correcting loop, watching them only at rest tells you little. You learn far more by gently challenging the system and watching how it responds and settles – which is precisely what the Kalmoa scan does.

A real-life example: To understand how a car runs, you can’t just observe it parked. You need to start the engine and listen to how it responds. With Kalmoa, a gentle, structured prompt reveals what quiet observation never would.

3. Emotions leave a bodily signature.

Emotions are not only experienced in the head; they are written into the body in consistent, recognizable ways. Antonio Damasio brought attention to this with his somatic marker hypothesis: that bodily states carry emotional meaning and even steer our decisions, often before we are aware of them 6. However, the strongest evidence came later, from large studies of thousands of people, across cultures as diverse as Finland and Taiwan, where participants were asked where in their body they feel different emotions. The resulting body maps were strikingly similar everywhere: anger, fear, love, and joy each activate the body in their own characteristic pattern, largely independent of language or culture 7. Underneath that emotional mapping lies measurable physiology: the autonomic nervous system shifts in structured, repeatable ways as emotions change 8, and those signatures fade or blur in conditions like depression. Because emotional states leave organized signatures rather than random noise, they can be recognized as patterns.

A real-life example: Anger warms the chest and hands; fear drains the limbs and knots the stomach. People describe feeling emotions in the same parts of their body whether they grew up in Helsinki or Taipei.
 

4. The brain and body respond to structured sound.

Sound is one of the best-studied inputs in psychophysiology (the science of reading the body to understand the mind). Carefully chosen sounds reliably tilt the balance of the autonomic nervous system and change heart-rate variability – the small, healthy beat-to-beat variation that is one of the most sensitive everyday markers of how well someone is coping with stress 9. The brain also synchronizes itself to musical structure, and music reliably evokes and shapes emotion through well-mapped brain systems 10. More surprising still: sounds we cannot consciously hear, the very high-frequency components of natural sound, still change brain activity and the body's automatic regulation, often without the listener noticing anything 11. Structured sound is a reliable, comfortable, and non-invasive way to produce measurable responses in the brain-body system. Which is exactly why Kalmoa uses it.

A real-life example: A piece of music gives you goosebumps, or a slow playlist quietly settles your breathing. You did not decide to react; your body responded to the sound on its own.

5. Validated reference models: Turning a number into meaning.

The first four pillars explain why a scan can pick up useful, measurable information. The fifth addresses the trustworthiness of such a system: once you have measured someone, how do you know it is measuring what you want it to measure? The established answer, used throughout medicine, is through rigorous comparison. You build a reference database, a large, well-characterized collection of measurements from many people. Then you work out what a normal range looks like, while accounting for factors like age and sex. From there, you can measure how far each new measurement sits from that norm. This is not new: decades ago, a paper in Science introduced an approach called neurometrics, which showed that comparing a person's brain measurements to such a database could distinguish clinical conditions with high accuracy 12. This method was later validated with rigorous statistical support 13. Kalmoa's reference model works on this principle, comparing your pattern to more than forty thousand reference scans. The larger and better-characterized this database becomes, the sharper the comparison and more reliable the results.

A real-life example: A body temperature of 37.5 means nothing on its own. It only becomes meaningful once you compare it to the normal range. A single scan works the same way: the reference database is what turns a reading into insight.
 

1 (Garfinkel et al., 2015; Craig, 2002; Critchley et al., 2004)
2 (Greenwood and Garfinkel, 2025)
3 (Critchley and Garfinkel, 2017; Quadt et al., 2018; Khalsa et al., 2018)
4 (Barrett and Simmons, 2015; Friston, 2010; Seth and Friston, 2016; Seth, 2013)
5 (Barrett, 2017)
6 (Damasio, 1996)
7 (Nummenmaa et al., 2014; Volynets et al., 2020)
8 (Kreibig, 2010)
9 (McConnell et al., 2014)
10 (Koelsch, 2014)
11 (Oohashi et al., 2000; Kuribayashi and Nittono, 2017; Jogasaki, Kawai, Nishina et al., 2025)
12 (John et al., 1988)
13 (Thatcher et al., 2003; Thatcher, 2010)

The chain, seen together

These five pillars form one chain of reasoning. The body and brain are in constant two-way contact, allowing us to measure that interaction. The brain actively regulates and predicts, so it can be probed rather than only observed. Emotional states leave organized bodily signatures, so there are genuine patterns to find. Structured sound is a reliable, non-invasive way to elicit those signatures. And comparisons to a large reference database turns  measurements into meaningful insights. None of these are speculative claims. They are well-established findings, produced independently by many research groups over decades, converging on a single conclusion: the body carries reliable, structured information about mental and emotional states, and that information can be measured, and turned into meaningful individual results. Kalmoa combines these established foundations into one integrated, practical tool for assessment.

Responsible by design

Kalmoa is built with privacy in mind, and designed to aid informed decision-making. It is meant to support human judgment rather than to diagnose. Its results are meant to be used alongside your own reflection and, where relevant, the expertise of a professional. Development is ongoing: Kalmoa is continuously working with independent partners to strengthen the evidence base behind the platform.

Experience Kalmoa for yourself!

Selected scientific references

Barrett, L. F. (2017). The theory of constructed emotion: an active inference account of interoception and categorization. Social Cognitive and Affective Neuroscience, 12(1), 1 to 23.

Barrett, L. F., and Simmons, W. K. (2015). Interoceptive predictions in the brain. Nature Reviews Neuroscience, 16(7), 419 to 429.

Craig, A. D. (2002). How do you feel? Interoception: the sense of the physiological condition of the body. Nature Reviews Neuroscience, 3(8), 655 to 666.

Critchley, H. D., and Garfinkel, S. N. (2017). Interoception and emotion. Current Opinion in Psychology, 17, 7 to 14.

Critchley, H. D., Wiens, S., Rotshtein, P., Ohman, A., and Dolan, R. J. (2004). Neural systems supporting interoceptive awareness. Nature Neuroscience, 7(2), 189 to 195.

Damasio, A. R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical Transactions of the Royal Society B, 351(1346), 1413 to 1420.

Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11(2), 127 to 138.

Garfinkel, S. N., Seth, A. K., Barrett, A. B., Suzuki, K., and Critchley, H. D. (2015). Knowing your own heart: distinguishing interoceptive accuracy from interoceptive awareness. Biological Psychology, 104, 65 to 74.

Greenwood, B. M., and Garfinkel, S. N. (2025). Interoceptive mechanisms and emotional processing. Annual Review of Psychology, 76, 59 to 86.

Jogasaki, K., Kawai, N., Nishina, E., et al. (2025). Enhancing the regulatory function of the autonomic nervous system using sounds with inaudible high-frequency components. Scientific Reports, 15, 26820.

John, E. R., Prichep, L. S., Fridman, J., and Easton, P. (1988). Neurometrics: computer-assisted differential diagnosis of brain dysfunctions. Science, 239(4836), 162 to 169.

Khalsa, S. S., Adolphs, R., Cameron, O. G., et al. (2018). Interoception and mental health: a roadmap. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3(6), 501 to 513.

Koelsch, S. (2014). Brain correlates of music-evoked emotions. Nature Reviews Neuroscience, 15(3), 170 to 180.

Kreibig, S. D. (2010). Autonomic nervous system activity in emotion: a review. Biological Psychology, 84(3), 394 to 421.

Kuribayashi, R., and Nittono, H. (2017). High-resolution audio with inaudible high-frequency components induces a relaxed attentional state without conscious awareness. Frontiers in Psychology, 8, 93.

McConnell, P. A., et al. (2014). Auditory driving of the autonomic nervous system: theta-frequency binaural beats increase parasympathetic activation and sympathetic withdrawal. Frontiers in Psychology, 5, 1248.

Nummenmaa, L., Glerean, E., Hari, R., and Hietanen, J. K. (2014). Bodily maps of emotions. Proceedings of the National Academy of Sciences, 111(2), 646 to 651.

Oohashi, T., Nishina, E., Honda, M., et al. (2000). Inaudible high-frequency sounds affect brain activity: the hypersonic effect. Journal of Neurophysiology, 83(6), 3548 to 3558.

Quadt, L., Critchley, H. D., and Garfinkel, S. N. (2018). The neurobiology of interoception in health and disease. Annals of the New York Academy of Sciences, 1428(1), 112 to 128.

Seth, A. K. (2013). Interoceptive inference, emotion, and the embodied self. Trends in Cognitive Sciences, 17(11), 565 to 573.

Seth, A. K., and Friston, K. J. (2016). Active interoceptive inference and the emotional brain. Philosophical Transactions of the Royal Society B, 371(1708), 20160007.

Thatcher, R. W., Walker, R. A., Biver, C. J., North, D. N., and Curtin, R. (2003). Quantitative EEG normative databases: validation and clinical correlation. Journal of Neurotherapy, 7(3 to 4), 87 to 121.

Thatcher, R. W. (2010). Validity and reliability of quantitative electroencephalography. Journal of Neurotherapy, 14(2), 122 to 152.

Volynets, S., Glerean, E., Hietanen, J. K., Hari, R., and Nummenmaa, L. (2020). Bodily maps of emotions are culturally universal. Emotion, 20(7), 1127 to 1136.