Why the Future of Health Measurement Is Longitudinal

From a Medical Snapshot to a Physiological Timeline

Medicine has become extraordinarily good at taking snapshots.

A blood panel captures selected chemistry at the moment the sample is drawn. An MRI or CT scan reveals anatomy at a particular point in time. An ECG records cardiac electrical activity during the period in which the patient is connected. A physical examination documents what the clinician can observe during one encounter.

These measurements are indispensable. They help identify disease, guide treatment and save lives.

But a snapshot cannot, by itself, show the direction in which a person is moving.

It cannot tell us whether today’s result represents a stable personal pattern, an early departure from baseline, a temporary response to stress, or the beginning of a sustained physiological change. Two people may produce the same laboratory value while arriving there through very different trajectories. One may have been stable for years. The other may have changed significantly over the preceding month.

The number may be the same. Its meaning may not be.

The future of health measurement will depend not only on knowing where a person is today, but on understanding how that person is changing over time.

The Body Is Not a Still Image

Human physiology is continuously adapting.

Sleep, nutrition, medication, infection, psychological stress, physical training and environmental exposure can alter the body’s state. Some changes resolve quickly. Others accumulate quietly. Still others may precede symptoms or recognizable disease.

Conventional medicine usually samples this dynamic system intermittently. A patient may receive laboratory testing once a year, imaging only after symptoms develop, and a clinical examination during an encounter lasting less than an hour. Important changes can occur between those measurements.

A normal result does not always mean that nothing is changing. It means that the variables measured at that moment remained within the reference limits established for that test. That is useful information, but it is not the entire physiological story.

What Wearables Have Already Taught Us

Wearable technology introduced medicine and the public to a different idea: health information becomes more meaningful when viewed as a trend.

A smartwatch or ring may repeatedly measure heart rate, heart rate variability, activity, sleep, temperature or blood oxygen saturation. None of these measurements provides a complete picture of health. Their value comes partly from repetition.

A single resting heart rate may reveal little. A persistent change from an individual’s established resting heart rate may deserve attention.

Research using wearable devices increasingly supports the importance of personal baselines. Heart rate, sleep, activity and autonomic measures can vary substantially between people while remaining comparatively stable within the same person. In several studies, changes relative to an individual’s baseline have been more informative than comparison with population averages alone.

The individual can become his or her own reference.

Wearables also have limitations. Most continuously monitor a relatively small group of variables. They are useful for showing how a few signals move across time, but they do not necessarily provide a broad, system-level physiological assessment. This creates an opportunity for another kind of measurement.

A Different Layer of Longitudinal Information

Aurorus is not a continuous wearable, nor is it intended to replace one.

It is a repeatable, non-invasive electrophysiological measurement platform. In under seven minutes, it captures an evoked electrophotonic response from the fingertips and converts features within that signal into quantitative information across 49 physiological and anatomical channels.

A single Aurorus scan remains a point-in-time measurement. Its greater potential emerges when the measurement is repeated.

The first scan establishes a baseline. Later scans can then be compared with that baseline under different conditions:

Before and after an intervention
During illness and recovery
Across medication or treatment changes
Before and after physical exertion
During periods of increased stress
Across a rehabilitation program
Before, during and after a clinical trial
Throughout deployment, travel or environmental exposure
Across months or years of preventive health monitoring

The objective is not simply to decide whether a score is good or bad. It is to determine what is changing, where it is changing, how quickly it is changing and whether the person is returning toward, or moving further away from, an established physiological baseline.

Why Personal Baselines Matter

Population reference ranges remain essential. They tell clinicians how an individual compares with a larger group and help identify values associated with known clinical risk.

But population averages can obscure meaningful individual change.

Imagine that a physiological measure has a population reference interval from 40 to 100. One person’s stable baseline may be 50. Another person’s may be 90. If the first person shifts from 50 to 78, the result could remain within the population range while representing a substantial departure from that individual’s history.

A system focused only on population thresholds may call the result normal. A longitudinal system would recognize the change.

This does not mean that every deviation represents disease. Physiology changes for many ordinary reasons, including meals, sleep, exercise, emotional stress, medication and time of day. A deviation creates a question that should be examined in context:

Is the change temporary or persistent
Is it isolated or visible across multiple physiological channels
Does it correspond with symptoms, laboratory values or another clinical finding
Did it begin after a treatment, exposure or behavioral change
Does it resolve when the suspected influence is removed
Is the individual recovering toward baseline

The purpose of longitudinal measurement is not to turn every fluctuation into an alarm. It is to make patterns visible.

From Isolated Results to Trajectories

The difference between a snapshot and a timeline is more than the number of measurements collected. A timeline creates new forms of information.

Longitudinal dimension	Question the timeline can address
Direction	Whether the physiological pattern is improving, deteriorating or remaining stable
Rate of change	Whether the shift occurred suddenly or accumulated gradually
Recovery	How quickly the person returns toward baseline after exertion, stress, illness or treatment
Response	Whether an intervention produced a measurable change and whether it was sustained
Variability	Whether repeated measurements are stable or fluctuate widely
Context	Whether changes correspond with sleep, medication, training, nutrition, emotional state or environmental exposure

These questions cannot be answered reliably from one measurement alone.

One Principle Across Multiple Settings

Hospitals and clinical care

Repeated measurements could help researchers characterize change across admission, treatment, discharge and recovery. The value would be another objective trend alongside laboratory testing, imaging and clinical judgment.

Wellness and preventive health

Periodic scans could contribute to a personal physiological history, allowing change to be recognized against previous measurements rather than starting from zero at every visit.

Sports and human performance

Measurements across training, competition, travel and recovery could support research into readiness, cumulative load and return toward baseline.

Clinical trials

Frequent, low-burden measurements could add a multidimensional trajectory alongside protocol-defined laboratory, imaging and clinical endpoints.

Spaceflight aviation and maritime medicine

A baseline established before departure could provide a reference during prolonged exposure to altered sleep, workload, isolation and environmental stress.

Defense and austere medicine

Portable serial measurement could support research into readiness, cumulative stress, injury response and recovery while remaining complementary to established medical protocols.

The instrument does not need to become a different product for every setting. The measurement remains consistent. The research question, evidence requirements and validation pathway change.

The Role of Artificial Intelligence

Longitudinal data also changes what artificial intelligence can learn.

A collection of isolated scans can help algorithms identify differences between groups. A longitudinal dataset adds the ability to study patterns of change within individuals.

With sufficiently standardized data, machine learning could investigate questions such as:

Which changes are normal for this person
Which deviations repeatedly accompany illness, stress or impaired recovery
Whether patterns appear before conventional findings
Which individuals respond to a particular intervention
Whether recovery trajectories can be distinguished from deterioration
Which features remain meaningful across sites, populations and devices

Artificial intelligence cannot create information that was never measured. Its value depends on the quality, consistency and clinical context of the underlying data.

The long-term Aurorus opportunity is therefore larger than applying AI to images. It is to build a structured, longitudinal physiological dataset in which each person’s measurements can be compared with conventional findings, interventions and outcomes over time.

Building the Timeline Responsibly

Longitudinal measurement is useful only when acquisition and interpretation are disciplined.

Meaningful analysis requires standardized procedures, device quality control and documentation of variables that can affect physiology, including medications, meals, exercise, sleep, acute illness and emotional state.

Research applications should pair Aurorus measurements with established comparators. Algorithms should be developed and validated on separate data. Findings should be independently reproduced, and performance should be evaluated across ages, sexes, sites and clinical conditions.

Most importantly, the technology’s current capabilities must remain clearly separated from future applications that require additional validation and regulatory authorization.

Aurorus provides non-invasive measurement of electrophysiological signals emanating from the skin under the device type classified by the FDA through DEN150004. It is not presently cleared to diagnose a specific disease or independently direct clinical decisions.

The opportunity is to determine, rigorously and transparently, how much clinically and physiologically useful information the signal contains.

A Different Question for the Future of Medicine

For much of medical history, the central measurement question has been whether a result is normal or abnormal compared with the population.

Longitudinal health measurement adds another question: Is this person meaningfully different from his or her own established state?

Both questions matter. Population evidence provides the clinical framework. Personal history provides the individual context. Conventional testing reveals specific structures, molecules and functions. Wearables show continuous movement in a limited number of variables. Aurorus is being developed to explore a complementary possibility: a repeatable, multidimensional view of physiological state that can be compared across time.

The future is not one test replacing another. It is different measurement layers working together.

A snapshot can tell us where a person is. A timeline may help us understand where that person is going.

Selected Scientific Context

Regulatory Note

Aurorus is a non-invasive electrophysiological measurement platform based on the device type classified by FDA under DEN150004. The cleared device is limited to measuring and documenting electrophysiological signals emanating from the skin and is not intended for diagnostic purposes or for independently influencing clinical decisions. The longitudinal applications discussed in this article include current research uses and proposed future applications that may require additional validation, independently designed studies and application-specific regulatory authorization.

End · 8 min

Nancy Rizzo Prior to developing the science and technology for Aurorus, Nancy spent 13 years at Mayo Clinic Scottsdale as a board certified radiological therapeutic physicist and cochaired the Complementary and Alternative Medicine program. Nancy is board certified as a Radiological Therapeutic Physicist by the American Board of Radiology (DABR) and holds a Ph D. in Energy Medicine with an emphasis on Biophysics from Holos University.

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