Revolutionising Emotional Health

Executive Summary

Emotional health is a critical yet under measured determinant of individual wellbeing, leadership effectiveness, and societal resilience. While consumer wearables generate vast amounts of physiological data and wellness apps encourage subjective mood tracking, no existing solution bridges these domains into a coherent, actionable model of emotional regulation.

INTRUTH is an emotion health platform that changes how people understand and manage their emotional wellbeing. By pairing biometric data from consumer wearables with purpose-built AI, INTRUTH delivers something no existing wellness app offers: real-time, physiologically-grounded insight into emotional states and the tools to improve them.

The platform delivers two core capabilities:

• Emotion Regulation Tracking: Most mental health tools stop at labeling how you feel. INTRUTH goes further, tracking how effectively users regulate their emotional responses, surfacing patterns in recovery time, trigger-response cycles, and which coping strategies actually work.
• Emotion State Monitoring: INTRUTH's AI integrates emotion-related physiological signals with user-reported context to identify and track emotional states over time. This goes well beyond simple mood logging, it's emotion detection informed by what the body is actually doing.

This combination of bridging the gap between biometric measurement and lived emotional experience, positions INTRUTH as the first platform to turn passive wearable data into meaningful, personalized emotional health insights.

Core Feature Summary

• Emotion Score: A personalised daily score reflecting your body's ability to regulate emotional responses, built on three dimensions validated against established measures of emotional wellbeing:
  • Capacity - Overall regulation throughout the day
  • Reactivity - How easily your system is triggered
  • Rebound - How quickly you recover once activated
• Multimodal Emotion Analysis: INTRUTH's AI journaling feature combines what you write about your emotional experiences with your body's physiological signals. By fusing these two sources of information, INTRUTH delivers a richer, more complete understanding of your emotional state than either source could provide alone.
• Real-Time Emotional Monitoring: Using heart rate (HR) and heart rate variability (HRV) data, INTRUTH measures how well your autonomic regulatory system is performing in real time — giving you immediate visibility into your current regulation capacity and how it shifts throughout the day.
• Historical Emotion Tracking: Gain a deeper understanding of your emotional patterns over time, allowing you to anticipate emotional shifts and take proactive steps for better emotional wellbeing.
• Event and Activity Correlation: Understand the triggers and activities that influence your emotional state, providing a holistic view of your emotional landscape.
• Personalised Self-Care Recommendations: Based on your emotional data and activity correlations, INTRUTH offers tailored self-care strategies that are grounded in scientifically proven methods, to assist you to improve your emotional and physical health.

Why INTRUTH?

INTRUTH aims to bring objectivity and actionable insights into the often nebulous realm of emotional health. By objectively measuring and interpreting physiological responses to environmental situations and concurrent thoughts that are expressed, it shines a light on unconscious factors that influence your daily life, providing an objective perspective on your emotional state, triggers and patterns. This level of self-awareness is crucial for maintaining a healthy style through effective emotional regulation, resilience building, and improved decision-making. Without the skill of emotional regulation, empathy in relationships and leadership more broadly is compromised, leading to fractured and disconnected systems.

Moreover, INTRUTH serves as a tangible indicator of personal growth and transformation, allowing users to track and measure their progress over time. This adds a layer of motivation and validation to their emotional and physical health journey.

By offering this comprehensive suite of features, INTRUTH supports users in transitioning from merely coping with emotional struggles to thriving in their emotional lives. This aligns seamlessly with Love Out Loud's vision of creating global awareness of emotional health as a cornerstone of overall wellbeing and societal transformation. INTRUTH is not merely a digital application, it represents a transformative initiative designed to advance pioneering a new conversation around emotional awareness, capacity, and resilience, within a broader health context. In short, it adds a missing data-driven infrastructure that will allow true system reform.

In the following sections of this white paper, we will delve deeper into the pressing need for a focus on emotional health in today's world, the science behind our application, and the unique features that make INTRUTH a pioneering tool. We will also discuss our research methodologies, validation studies, and future developments. This comprehensive document aims to provide potential partners and stakeholders with a thorough understanding of INTRUTH's capabilities, its alignment with Love Out Loud's broader mission, and its potential to significantly impact emotional health on a global scale.

Introduction: The World in Disarray

Contemporary society is characterised by significant deficits in health and social cohesion, underscoring the necessity for change. We find ourselves in an era characterised by a significant increase in the prevalence of chronic diseases, encompassing both physiological and psychiatric conditions. According to the World Health Organization, non-communicable diseases like heart disease, stroke, and diabetes are responsible for 71% of all deaths globally[1]. The Centers for Disease Control and Prevention (CDC) further highlight the gravity of the situation, stating that more than 1 in 5 U.S. adults live with a mental illness[2], and 6 in 10 adults in the U.S. live with a chronic disease[3]. These staggering statistics are more than just numbers; they are a reflection of widespread dysfunction in societal structures, due to a disconnect from established health principles and determinants of well-being.

This dysfunction extends beyond physical and mental health, manifesting as increased social polarisation. The loss of social cohesion contributes to an environment characterised by reduced tolerance and exacerbated psychological distress. Individuals may experience heightened feelings of shame, guilt, and unmet emotional needs, leading to increased social isolation and impaired mental well-being.

The avoidance of open and empathetic dialogue further creates greater disconnection and hinders the development of supportive interpersonal relationships, which are essential for emotional health.

Literature by Agnese Mariotti states that emotional stress is a major cause of physical illness, intricately connected with the endocrine, metabolic system, and particularly the immune system[4]. Social stigmas around emotional vulnerability and mental health further complicate the issue, making it difficult for people to seek help or to understand the underlining causes of these emotional triggers.

Contemporary society is characterised by rapid changes, pervasive technology, and weakened social bonds. These factors collectively present significant challenges to achieving personal wellbeing and social cohesion.

In the following sections, we will delve into the overlooked yet crucial discussion of emotional health.

The Overlooked Solution: Emotional Health

Within the complexity and rapid changes of contemporary society, an essential aspect that is frequently overlooked is emotional health. Although substantial progress has been achieved in the study and treatment of physical health conditions, the area of emotional well-being and the psychological factors that influence it, continues to be insufficiently investigated and often overlooked.

Yet, it is this very aspect of human existence that holds the key to unlocking a better individual and collective societal future for all. Emotional health is not just about managing stress or avoiding negative emotions; it's about achieving a state of emotional awareness and equilibrium where individuals can navigate the complexities of life with emotional regulation, resilience, empathy, and a deep sense of self-awareness.

At INTRUTH, born as the innovation arm of the wider movement 'Love Out Loud', we are committed to filling this gap by building emotionally healthy social entrepreneurs, leaders, health practitioners and individuals. We believe that by fostering emotional health at an individual level, we can create a ripple effect that will lead to collective change. Our mission is grounded in the understanding that emotionally healthy individuals are better equipped to address the underlying causes, rather than merely the symptoms of the challenges that impact society. They are the change-makers who can navigate their own emotional health, divisive social landscapes, build bridges between communities, and create solutions that are holistic and sustainable.

Our Theory of Change

Our theory of change is simple yet profound: Emotional regulation leads to behavioural change, which in turn leads to collective change. When individuals are emotionally healthy, they are more likely and more capable to engage in behaviours that are beneficial not just for themselves but for society at large. They become more balanced, empathetic, collaborative, and open to different perspectives. This behavioural change can propagate through social networks, motivating others to pursue improvements in their own emotional wellbeing.

As participation in this collective movement increases, these changes can spread through communities, leading to a society that appreciates emotional intelligence just as much as knowledge and skills. This helps create an environment where people can truly thrive.

In the subsequent sections, we will delve deeper into what emotional health means, how it influences our physical health and decision-making processes, and why it is the missing link in many of the conversations we are having today about health, politics, and social justice. We will also introduce INTRUTH, our personalised, AI-assisted emotional health tool designed to empower individuals on their journey toward emotional well-being.

Defining Emotional Health

Emotional health, often overshadowed by its more discussed counterparts, mental and physical health, stands as a distinct and crucial aspect of overall well-being. It involves a nuanced understanding of one's emotions, the ability to manage them effectively, and the skill to express them constructively. While mental health focuses on cognitive patterns and psychological disorders, and physical health zeroes in on bodily functions and metrics, emotional health functions as a central factor that significantly influences and informs the overall quality of life.

Emotional health is about our relationship with our emotions, how we understand them, how we manage them, and how they influence our actions and interactions. It also takes into account the physiological signals, recognizing the often unconscious nature of how the nervous system drives these emotional sensations in the body.

Unpacking Emotional Health

At INTRUTH, we define emotional health into three interconnected areas, each contributing to the broader state of emotional well-being:

• Emotional Awareness: This is the foundational skill for recognizing emotions. It involves being conscious of what you're feeling, why you're feeling it, and how it's affecting your thoughts and behaviours. Emotional awareness is crucial for navigating social situations and for self-regulation.
• Emotional Precision: This adds nuance to how we identify and talk about emotions. Instead of just saying you're "feeling bad," you'd be able to specify whether you're "frustrated," "anxious," "disappointed," etc. The more granular your emotional vocabulary, the better you can understand your emotional experiences, which in turn can help you regulate your emotions more effectively. Research supports the importance of identifying specific emotions in coping behaviors and capabilities. For instance, a study found that greater emotional precision was associated with larger repertoires of emotion-regulation strategies as well as the ability to elicit positive emotions in close others[5].
• Emotional Capacity: This speaks to our ability to handle a range of emotional experiences and build resilience. It's the psychological and physiological resilience to respond to challenges, adapt to change, and bounce back to a state of emotional balance once the situation has passed. A lack of emotional capacity makes us reactive and easily stuck in fight, flight, or freeze responses.
• Emotional Intelligence: Often defined as "the willingness and capacity to be present in any and all situations," emotional intelligence is about your skill set for dealing with emotions, both yours and those of others. It allows us to manage and apply our emotional awareness, granularity, and capacity effectively in different situations with others such as influencing, coaching, mentoring, and conflict resolution.
• Identity: This is the broader state of well-being that includes aspects like authenticity, self-esteem, confidence, unwavering belief in oneself, the ability to recognize one's needs and meet them, to ask for what one wants, and to be vulnerable.

By understanding and cultivating these five areas, individuals can achieve a state of emotional health that not only benefits them personally but also has far-reaching implications for their mental and physical well-being. This comprehensive approach to emotional health is supported by scientific evidence, making it not just a theoretical construct but a validated framework for human flourishing, as further discussed below.

Emotional Health and Decision Making

The influence of emotional well-being on decision-making processes is well established in the scientific community, indicating that its importance extends beyond intuitive understanding and is grounded in robust scientific findings. Research conducted by J. Lerner and colleagues[6] analysed 35 years of data on emotions and decision making, which revolutionised our understanding of the role emotions play in our choices. The paper introduces an "emotion-imbued choice model," which synthesises traditional rational choice theory with cutting-edge emotion research. According to this model, emotions are "potent, pervasive, predictable drivers of decision making." They guide our daily attempts to avoid negative feelings like guilt and regret while enhancing motivation and amplifying positive feelings such as pride and happiness. The paper goes on to assert that "emotions powerfully, predictably, and pervasively influence decision making."

The research highlights the significant influence of emotions on decision-making, suggesting that emotional intelligence plays a crucial role in effective leadership. The findings indicate that emotionally healthy leadership may contribute positively to organisational and societal outcomes. Therefore, fostering emotional intelligence among leaders in various institutions could be beneficial for decision-making processes and overall societal well-being.

The paper also discusses emotion-specific "action tendencies." For example, anxiety, characterised by facing both real and perceived uncertain existential threats, leads to a tendency to reduce uncertainty and reduce risk. In contrast, sadness, characterised by experiencing irrevocable loss, accompanies a tendency towards reward seeking behaviour and thus a higher appetite for risk. This nuanced understanding of how different emotions drive different types of decisions further emphasises the complexity and importance of emotional health.

Moreover, the research highlights the "carryover" effect of emotions, where emotions triggered in one situation can influence decisions in completely unrelated scenarios. This is particularly relevant in today's hyper-connected world, where we are constantly bombarded by stimuli which necessarily generate emotions. The paper even cites studies showing that something as simple as the amount of sunshine on a given day can influence stock market performance. This underscores the pervasive impact of emotional health on various aspects of society, from economics to politics.

In summary, studies have demonstrated that affective processes substantially impact cognitive functions involved in decision-making. Emotional intelligence, defined as the capacity to perceive, integrate, understand, and regulate emotions, has been identified as a key factor in effective leadership. Evidence suggests that leaders exhibiting higher levels of emotional intelligence are associated with improved organisational performance and enhanced social outcomes. Consequently, the development and application of emotional intelligence within leadership contexts may facilitate more adaptive decision-making and promote collective well-being.

The Science of Emotion Regulation: From Response to Recovery

When an environmental demand arises, a stressful conversation, an unexpected deadline, a perceived threat, the autonomic nervous system mobilizes rapidly. Subcortical circuits, particularly the amygdala, trigger a coordinated physiological response: heart rate rises, heart rate variability drops, and the body prepares for action. This happens within milliseconds, often before conscious awareness[7].

This response is not the problem. It is adaptive, a system evolved to protect us. The critical question for mental health is what happens next: how effectively does the system stand down once the demand has passed?

Multiple converging lines of research point to the same conclusion: psychological vulnerability is defined not by how strongly the system reacts, but by how poorly it recovers.

Why Recovery Dynamics Define Vulnerability

The concept of affective chronometry[8] formalized what clinicians had long observed: emotional responses can be characterized by their temporal dynamics, how easily they are triggered, how quickly they peak, and critically, how rapidly they resolve. Davidson's key insight was that recovery time is the most diagnostically important parameter. Individuals vulnerable to depression and anxiety show prolonged recovery from negative affect, not necessarily greater initial reactivity. Neuroimaging work has since confirmed that these individual differences in recovery are linked to specific properties of prefrontal-amygdala circuits, the same circuits indexed by HRV[9].

This aligns with the concept of allostatic load[10] the cumulative biological cost of chronic stress. Allostatic load doesn't accumulate from stress responses per se, but from specific failures of the regulatory system: failure to habituate to recurring stressors, and failure to terminate the stress response after the threat has passed. The acute response is protective; it is the inability to resolve it that becomes pathological.

Gross's process model of emotion regulation[11], the most widely cited framework in the field, describes the strategies people use to modulate emotional responses, from situation selection through cognitive reappraisal to response suppression. A consistent finding across meta-analyses is that strategies deployed earlier in the emotional cascade, particularly cognitive reappraisal, produce better psychological outcomes than late-stage strategies like suppression[12]. This has direct implications for intervention design: the earlier you can support the regulatory process, the more effective the outcome.

Why This Matters: Regulation Is Measurable and Modifiable

The neurovisceral integration model[13] provides the bridge between these psychological frameworks and what a wearable can measure. Because the prefrontal circuits that regulate emotion also regulate cardiac vagal tone via the vagus nerve, heart rate variability serves as a peripheral index of central regulatory capacity. Meta-analyses confirm reduced HRV across anxiety disorders[14] and depression[15] with consistent small-to-moderate effect sizes.

Crucially, these regulation patterns are not fixed. The neural circuits underlying emotion regulation are demonstrably plastic:

• Cognitive-behavioral interventions alter reappraisal capacity and reduce maladaptive regulation strategies[16]
• Mindfulness-based interventions modify both deliberate and automatic regulation processes, with measurable changes in prefrontal-amygdala connectivity[17]
• HRV biofeedback, directly relevant to wearable-based intervention shows medium effect sizes for depressive symptoms and HRV improvement across randomized controlled trials[18] with recent evidence that remote delivery via consumer devices is comparably effective to in-person protocols

This is the scientific foundation for INTRUTH's approach: regulation dynamics are the most meaningful signal in continuous autonomic data, they are strongly linked to mental health outcomes, and they are modifiable through targeted intervention. A system that can measure regulation performance in real time, and deliver that information back to the user, sits at the intersection of decades of affective science and the emerging infrastructure of consumer wearables.

The Experience of Emotion: A Multi-Level Framework

Emotional experience emerges from the continuous interaction of multiple systems operating at different levels. This is not unique to any single theory — it is a point of convergence across affective science. Whether framed through Barrett's theory of constructed emotion,[19] Gross's process model of emotion regulation,[11] or the neurovisceral integration model,[13] the same architectural insight holds: emotional experience is shaped by bottom-up physiological signals, top-down cognitive processes, and external environmental context, all operating in a continuous feedback loop.

Understanding these levels matters because each represents a distinct point of intervention — and different regulation practices target different levels of the system.

Bottom-Up: The Autonomic Nervous System

The body's first response to any environmental demand is physiological. Subcortical circuits detect salient stimuli and trigger rapid autonomic changes — shifts in heart rate, respiration, muscle tension, and arousal — before conscious appraisal has occurred[7]. These are not noise; they are the raw material of emotional experience. In the neurovisceral integration framework,[13] the quality of this bottom-up signaling — how flexibly the autonomic system shifts between activation and recovery — reflects the integrity of central regulatory circuits.

Regulation practices at this level target the body directly: breathwork, physical movement, nutrition, and sleep hygiene. These interventions work by modulating autonomic tone — for example, slow-paced breathing at ~6 breaths per minute stimulates the baroreflex, enhancing parasympathetic activity and improving vagal tone[20]. HRV biofeedback operates at this level, with randomized controlled trials demonstrating medium effect sizes for both autonomic improvement and symptom reduction[18].

What INTRUTH measures here: The regulation model continuously tracks autonomic dynamics — capacity, reactivity, and rebound — providing an objective readout of how the physiological system is performing in real time. This gives users visibility into whether bottom-up regulation is functioning well or degraded.

Top-Down: Cognitive Appraisal and Regulation

The same physiological arousal can produce very different emotional experiences depending on how the brain interprets it. A racing heart before a presentation can be experienced as anxiety or excitement — the autonomic signature is similar, but the cognitive framing transforms the experience. This is where prefrontal cortical regions apply learned expectations, contextual information, and regulatory strategies to modulate the automatic response.

Gross's process model[11] identifies a sequence of cognitive regulation strategies, from situation selection (choosing to avoid a trigger) through attentional deployment (redirecting focus) to cognitive reappraisal (reframing the meaning of a situation). A key meta-analytic finding is that earlier-stage strategies — particularly reappraisal — are consistently associated with better psychological outcomes than later-stage strategies like suppression[12]. Importantly, regulation operates on a spectrum from deliberate to automatic: practiced strategies can become habitual over time, shifting from effortful prefrontal control to more automatic regulation[21].

Regulation practices at this level: Include cognitive-behavioral therapy, mindfulness meditation, reframing techniques, and journaling. These interventions strengthen prefrontal regulatory capacity, with measurable changes in prefrontal-amygdala connectivity observable after 8 weeks of mindfulness training[17].

What INTRUTH provides here: The Emotion Language Model integrates journal text and contextual data with physiological signals, connecting autonomic dynamics to the user's cognitive and experiential world. This bridges the gap between what the body is doing (bottom-up) and what the person is experiencing (top-down), enabling personalized insight into how cognitive context shapes physiological response patterns.

Outside-In: Environmental Context

Both bottom-up and top-down processes are continuously modulated by the external environment — social context, physical surroundings, noise, light, time of day, and the demands of the situation. Environmental factors influence autonomic tone directly (e.g., noise exposure elevating sympathetic activation) and shape the cognitive frame through which physiological signals are interpreted.

This layer is often underappreciated in emotion regulation research, which has historically focused on internal processes. But real-world regulation happens in context: the same person may regulate effectively in a supportive environment and poorly in an adversarial one. Circadian rhythms modulate autonomic baseline and regulatory capacity throughout the day. Social interactions can either buffer or amplify stress responses.

What INTRUTH captures here: By collecting continuous data across real-world contexts — work, rest, exercise, social interaction — INTRUTH's models capture how regulation dynamics shift across environments. This ecological approach reveals patterns invisible to lab-based assessment: which contexts degrade regulatory performance, which support recovery, and how these patterns differ across individuals.

The Integration: Why All Three Levels Matter

The interaction between these levels is what produces both healthy and maladaptive emotional functioning. A well-regulated system responds flexibly: the autonomic system mobilizes when needed (bottom-up), cognitive appraisal contextualizes the response appropriately (top-down), and the environment supports recovery (outside-in). Dysfunction at any level — persistent autonomic activation, maladaptive cognitive patterns, or chronic environmental stressors — can degrade the whole system.

INTRUTH's architecture mirrors this multi-level reality:

This multi-level approach reflects the scientific consensus that emotion regulation is not a single process but an interacting system — and that effective intervention requires understanding which level to target for each individual.

The Gap in Existing Solutions

The current landscape of health and wellness tools, particularly smartwatches and smart rings, offers a plethora of devices that excel in tracking physical metrics like sleep, steps, and calories. However, when it comes to emotional well-being, these tools fall short. Most devices may tell you that you had poor sleep but offer no insights into why that might be the case or how to improve it.

Brands like Oura Ring, Fitbit, and Garmin utilise sophisticated consumer-grade biometric measurements but primarily focus on sleep and fitness. When it comes to emotional measurement, these tools are severely lacking. The most common approach to digital emotional tracking is a rudimentary 5-point pleasantness scale, as seen in Apple Watch and mood-tracking apps like Daylio. These tools rely on subjective self-reporting rather than objective measurement.

Heart Rate Variability (HRV) is another metric that has gained attention, especially for measuring nervous system readiness and recovery. Fitbit, for instance, uses HRV but only from a fitness perspective of exercise readiness. Physiological response monitoring is also becoming more common, with devices using heart rate and Galvanic Skin Response (GSR) to indicate outcomes like stress levels. However, these features are often binary, merely indicating whether the user is stressed or not, without delving into the 'why' or offering solutions.

Crucially, no existing consumer solution combines physiological measurement with the rich emotional context that comes from a person's own words. Wearable devices measure the body, and journaling apps capture thoughts—but these two worlds remain separate. INTRUTH is the first platform to fuse these complementary data streams into a unified emotional picture, bridging the gap between what the body reveals and what the mind expresses.

Why INTRUTH Is Different

500M+ wearables are collecting autonomic data. None of them interpret how well the regulatory system is actually performing.

Current devices report raw signals — a heart rate number, an HRV reading, a binary stress score. But these tell you nothing about the dynamics of your autonomic regulation: how easily your system is destabilized, how quickly it recovers, or how much regulatory capacity you have on a given day.

INTRUTH has built the regulation intelligence layer that sits on top of existing wearable hardware. Our proprietary model transforms raw HR and HRV data into three clinically grounded dimensions of regulatory performance:

• Capacity — baseline resilience. How much regulatory bandwidth does the system have?
• Reactivity — sensitivity to perturbation. How easily is the system destabilized?
• Rebound — recovery speed. When the system is activated, how quickly does it return to baseline?

This is a critical distinction. Rather than attempting to detect discrete emotional states from wrist-based sensors — an area where results remain mixed — we measure the performance characteristics of the autonomic regulatory system itself. This is scientifically stronger ground: validated against clinical measures of anxiety (GAD-7) and depression, with research demonstrating that the interaction between reactivity and rebound explains over 60% of variance in anxiety symptoms.

The result is an objective, continuous measure of regulation quality — not a mood label, but a window into how well the system that governs mood is functioning.

Why HRV: The Neurovisceral Integration Framework

The model is grounded in the Theory of Neurovisceral Integration[13] which provides the mechanistic bridge between what a wearable can measure and what clinically matters.

The core principle: vagally-mediated HRV indexes prefrontal inhibitory control over subcortical arousal circuits. When prefrontal-vagal regulation is robust (high HRV), the autonomic system shifts flexibly between sympathetic and parasympathetic states — mounting responses when needed and resolving them efficiently. When compromised (low HRV), the system remains locked in sympathetic dominance, paralleling the sustained activation that characterizes anxiety and poor regulation.

Neuroimaging research confirms that higher resting HRV corresponds to stronger prefrontal-amygdala connectivity, and meta-analyses show reduced HRV across anxiety and depression. Continuous HRV monitoring therefore captures individual differences in regulatory capacity without requiring explicit cognitive tasks or lab-based equipment.

But static HRV metrics alone are insufficient — established research shows they capture only modest associations with psychological outcomes. What INTRUTH's model captures are the temporal dynamics: not just your HRV level, but how the regulatory system behaves over time — how it reacts, how it recovers, and how those two processes interact. This is the signal that existing wearables miss entirely, and it's what 3+ years of research have enabled us to extract from consumer-grade hardware.

From Regulation to Meaning: The Emotion Language Model

The regulation model measures how well the autonomic system is performing. But users also need to understand what's happening, to connect physiological dynamics to lived emotional experience. This is the role of INTRUTH's Emotion Language Model: a multimodal AI system that integrates physiological signals with contextual data to produce interpretable emotional insights.

The Multimodal Approach

A core challenge in affective computing is that physiological signals and language carry fundamentally different emotional information. Research consistently shows that physiological data (HR, HRV) strongly reflects arousal — the activation level of the autonomic system but cannot distinguish valence (whether an experience is positive or negative). A racing heart accompanies both excitement and fear. Conversely, natural language is rich in valence information but often ambiguous about physiological activation.

INTRUTH's Emotion Language Model solves this by fusing both modalities using Russell's circumplex model of affect — a well-established psychological framework that maps emotional states along two continuous dimensions:

• Valence (positive ↔ negative) — primarily extracted from user journal entries and contextual text
• Arousal (activated ↔ deactivated) — primarily inferred from physiological signals relative to each individual's baseline

This early-fusion approach produces richer emotional characterization than either modality alone. Validated against established benchmark datasets (EmoBank for text, CASE for physiology), the multimodal system achieves 62% quadrant accuracy — compared to 47% from text alone and 33% from physiology alone. The complementary nature of these signals is the key insight: text tells us the direction of an emotional experience; physiology tells us its intensity.

Why This Matters for the Product

The Emotion Language Model transforms regulation data from clinical abstraction into personal meaning. When the regulation model detects a sustained activation episode with slow rebound, the Emotion Language Model can contextualize it: was this a stressful work meeting or an exciting creative session? Both produce similar autonomic signatures — the difference lies in the user's experience, captured through journaling and contextual data.

This creates two layers of intelligence from the same wearable data:

• Regulation layer — objective measurement of autonomic performance (capacity, reactivity, rebound)
• Meaning layer — contextual interpretation connecting physiological dynamics to emotional experience

Together, these layers power the Emotion Score — a composite that reflects not just raw physiological state, but regulation quality in the context of lived experience. The system is built with FDA 21 CFR Part 11 compliance in mind, with full audit trails and reproducible outputs.

Continuous Improvement

Every user interaction — each journal entry paired with physiological data — strengthens the model's ability to interpret the relationship between autonomic signals and emotional context. This is the data flywheel in action: the Emotion Language Model improves not through generic training data, but through real-world multimodal pairs that no other consumer platform is collecting at scale.

Target Audience

While we firmly believe that INTRUTH has universal applicability, essentially, anyone with emotions could benefit from it—our primary target audience is more specific. We aim to serve clients of aligned coaches and health practitioners who are already invested in the importance of emotional health as a component of overall well-being and performance. These professionals can integrate INTRUTH into their existing practices as an additional tool to aid in their clients' healing and self-improvement journeys.

Our go-to-market strategy initially focused on primarily B2B2C, targeting organisations and practitioners who can disseminate INTRUTH within their communities. This approach allowed us to reach a wider audience more efficiently, leveraging the trust and authority these organisations already have within their networks.

The second market release allowed individual end-users to access the INTRUTH app. We envision the target user is someone who has experienced the detrimental effects of poor physical, and emotional health. They are likely to be proactive in seeking solutions and may already be engaged in various healing modalities. INTRUTH serves as a precision general wellness tool that can be used either independently or in conjunction with other therapies and interventions. By focusing on this target audience, we aim to make a meaningful impact in the field of emotional health, offering a practical, science-backed tool for self-awareness and self-improvement.

The INTRUTH platform is engineered with a focus on user-centric design, ensuring that the interface is intuitive and conducive for emotional health monitoring. The ease of navigation is crucial, as we aim for users to spend less time figuring out the app and more time gaining insights into their emotional well-being.

Emotional Monitoring

We've incorporated real-time emotional monitoring to offer immediate, actionable insights. This feature is grounded in the Theory of Neurovisceral Integration, capturing changes in HR and HRV to provide a snapshot of the user's current emotional state. The immediacy of this data is crucial for users to understand and manage their emotions as they occur, thereby enhancing emotional regulation techniques.

Historical Emotion Tracking

Understanding emotional trends over time is vital for long-term emotional health. This feature aligns with our broader vision of empowering individuals to recognize patterns and anticipate emotional shifts. By doing so, users can proactively employ emotional regulation techniques, contributing to improved emotional resilience and capacity.

Event and Activity Correlation

We believe that emotional health is influenced by a myriad of factors, both internal and external. This feature aims to correlate emotional data with specific events or activities, offering users a more holistic understanding of their emotional landscape. This is particularly beneficial for coaches and health practitioners who can use this data to tailor interventions for their clients.

Personalised Self-Care Recommendations

In line with our mission to provide a comprehensive emotional health platform, we offer personalised self-care recommendations. These are generated through machine learning algorithms that analyse historical emotional data and activity correlations. The goal is to provide users with actionable steps that are grounded in objective data, thereby enhancing the efficacy of emotional regulation techniques.

Journaling and Calendar Integration with AI Analysis

INTRUTH's journaling feature serves a dual purpose: it aids users in emotional processing and feeds into our multimodal emotion analysis system. When users journal, their words are analysed alongside their concurrent physiological data to provide a complete picture of their emotional experience. The AI identifies key themes, patterns, and emotional qualities in the text, while the physiological data grounds these insights in the body's actual response. This fusion of subjective experience and objective measurement enables INTRUTH to surface insights that neither source alone could provide—helping users develop greater emotional precision and facilitating more meaningful conversations around emotional health.

This suite of features is designed to address multiple facets of emotional experience, from physiological to cognitive and environmental influences. We believe that this comprehensive approach will make INTRUTH an invaluable tool for coaches, health practitioners, and organisations committed to improving general emotional wellness.

Roadmap

As we continue to evolve and refine INTRUTH, our roadmap is a dynamic and evolving plan, reflective of our commitment to innovation and responsiveness to user needs. Currently, we are in the exciting phase of continuously gathering user market feedback from the release of the generation 1 INTRUTH app. Our focus remains on enhancing the user experience, expanding the capabilities of our technology, and exploring new research avenues to ensure that INTRUTH remains at the forefront of emotional health technology.

Safety and Privacy

At Love Out Loud, we hold a deep commitment to data sovereignty and the ethical handling of user information. We understand the sensitive nature of emotional data and prioritise the privacy and security of our users above all else. Our approach to data management is guided by the principles of transparency, consent, and control:

• Transparency: We ensure that our users are fully informed about the data we collect and how it is used.
• Ethics and Consent: Data is collected ethically and only with the express permission of our users. We believe in empowering our users to make informed decisions about their data.
• Privacy and Control: Users have the ultimate control over their data, including the ability to access, manage, and delete their information at any time. Their data remains private at all times.

We are continuously working to implement robust data protection measures that align with global standards and best practices, ensuring that our users' data is handled with the utmost care and respect.

Conclusion

Consumer wearables now generate continuous autonomic data during everyday life. AI systems can extract emotional context from natural language. The science of emotion regulation has identified what to measure — not static snapshots, but the temporal dynamics of how the system responds and recovers. These threads have not been brought together until now.

INTRUTH integrates them into a single platform. The regulation model extracts personalized measures of capacity, reactivity, and rebound from wearable HRV data — validated against clinical measures of anxiety, with peer-reviewed research showing that the interaction between reactivity and recovery dynamics predicts symptom severity. The Emotion Language Model fuses physiological signals with journal text and contextual data, connecting autonomic dynamics to lived emotional experience.

Together, these produce something that has not previously existed outside the research lab: continuous, objective, personalized measurement of how well the autonomic regulatory system is functioning — contextualized by the user's own experience.

The regulation intelligence layer didn't exist in the wearable ecosystem today.

We built it.

References