After moving beyond VR as the only possible outcome, I needed to understand the physiological side of the system more carefully. If I am considering technology that can respond to changes in the body, I need to know what those signals can actually tell me and where their limitations are.

The term biosignal covers physiological information that can be measured from the body. Across the papers I have been reading, this includes heart rate, heart rate variability, electrodermal activity, respiration and EEG. These signals are interesting because they can change alongside stress, cognitive demand and emotional arousal, potentially providing information that is not dependent on somebody verbally explaining how they feel.

However, the more I read, the clearer it becomes that physiological arousal is not the same thing as sensory overload.

Heart Rate Variability

One signal that appears repeatedly in the research is Heart Rate Variability, or HRV. HRV describes variation in the timing between heartbeats and is commonly used as an indirect indicator of autonomic nervous system activity.

I read Bahameish et al. (2026), Comparative Analysis of Heart Rate Variability Across Cognitive Domains in Individuals with Autism and ADHD: A Systematic Review and Meta-Analysis. The review included 20 studies and 2,223 participants, comparing HRV during cognitive tasks across autistic, ADHD and neurotypical populations.

The overall effect across all included neurodevelopmental groups was not statistically significant compared with neurotypical participants, although the autism subgroup showed a significant difference. What is more important for my project is that the authors identify substantial heterogeneity and methodological inconsistency between studies.

This means I cannot treat HRV as a simple or universal marker of an autistic person's regulatory state.

The Autonomic Nervous System

The paper helped me understand why HRV is relevant in the first place. The autonomic nervous system includes the sympathetic and parasympathetic systems. The sympathetic system is associated with mobilisation and "fight or flight", while the parasympathetic system supports rest, recovery and energy conservation.

HRV is connected to this balance, which is why it is often explored in research around stress, cognition and emotional regulation.

For my project, this makes HRV interesting because an airport involves repeated changes in cognitive and sensory demand. Security, navigation, queues, crowds and unexpected changes could all influence the body's physiological state.

But this is also exactly why interpretation becomes difficult.

A Change Does Not Explain the Cause

The same physiological signal can change for many reasons. A traveller's heart rate could rise because they are becoming overwhelmed, but it could also rise because they are walking quickly to a gate, carrying luggage, feeling excited, drinking caffeine or responding to another emotional or physical demand.

The anxiety-detection review reinforced this problem by warning against assuming that physiological markers can cleanly separate anxiety from other psychological states. Different measures also do not always agree with one another.

This is particularly important inside an airport because the environment is both physically active and cognitively demanding. A responsive system would need to understand physiological information in context rather than treating one number as a direct instruction to intervene.

Why Baseline Matters

This has made the idea of an individual baseline much more important to me. If people naturally have different heart-rate patterns and physiological responses, comparing everyone against the same threshold would make little sense.

A more appropriate system might need to understand what is typical for the individual and identify meaningful changes relative to their own baseline. Even then, that information would still need to be interpreted alongside what the person is doing and the context they are in.

This connects strongly with my wider autism research. I have repeatedly found that there is no single autistic sensory profile, so it would be contradictory to design a physiological system that assumes there is one universal biological response as well.

Other Biosignals

HRV is only one possibility. The machine-learning literature also describes the use of ECG, electrodermal activity, respiration, temperature and EEG. Combining several signals may potentially provide more information than depending on a single measure.

This introduces the idea of multimodal sensing, where different forms of data are considered together. For my project, this may eventually be more appropriate than designing around heart rate alone, although I need to remain realistic about what can be prototyped within a graphic-design master's project.

At this stage, the important thing is not to decide which sensor I will use. It is to understand the principle that physiological data is an additional source of information rather than a direct reading of emotion or overload.

What This Changes in My Project

This research makes the project more complex, but also more credible.

I am no longer imagining a wearable that simply detects that somebody is overwhelmed and automatically reacts. Instead, I am beginning to think about a system that notices changes in physiological state and uses them as one piece of information alongside individual baseline, context and user preference.

This also changes the role of AI within the project. AI would not be valuable because it can supposedly "know" how an autistic traveller feels. Its potential value would be in helping make sense of several changing inputs and supporting a more personalised response.

The design question therefore becomes less about detection and more about interpretation:

How could a system recognise meaningful physiological change without assuming that it fully understands the person's experience?

Key Terminology

Biosignal — measurable physiological information produced by the body.

Physiological arousal — changes in bodily activation associated with factors such as stress, emotion, cognitive effort or physical activity.

Heart Rate Variability (HRV) — variation in the time interval between heartbeats.

Autonomic Nervous System (ANS) — the system that regulates involuntary bodily processes, including heart rate and other physiological functions.

Sympathetic nervous system — part of the autonomic nervous system associated with mobilisation and responses such as "fight or flight".

Parasympathetic nervous system — part of the autonomic nervous system associated with rest, recovery and energy conservation.

Individual baseline — a person's own typical physiological pattern used as a reference point rather than comparing everybody against the same fixed threshold.

Multimodal sensing — combining several different forms of physiological or behavioural data to create a broader picture of changing state.