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Exercise physiologists

Also called Clinical exercise physiologist, CEP, ACSM-CEP, Cardiac rehab exercise physiologist, Cardiac rehabilitation specialist

In brief

In May 2025, BLS counted 8,560 US exercise physiologists, with median pay of $59,460 a year. Of the BLS counts since 2013, the May 2025 count is the highest. The earliest figure here is an estimate of 20 from 1927, not measured the same way as today's count. The last full technology era for exercise physiologists: Wearable cardiac monitors and consumer-grade biosensors, 2015 to 2023.

What the sources say

Official outlook

BLS projects employment to grow 12.8% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Exercise physiologists: jobs and pay since 1927 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/29-1128

Chicago

Future History. "Exercise physiologists: jobs and pay since 1927." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/29-1128.

BibTeX

@misc{futurehistory_29_1128, author = {{Future History}}, title = {Exercise physiologists: jobs and pay since 1927}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/29-1128}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

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195019752000now
2026
Known then as Exercise Physiologist / Physiologist of Work (academic research era, Harvard Fatigue Laboratory)
Known then as Clinical Exercise Physiologist / Cardiac Rehabilitation Specialist (ACSM era, pre-Medicare coverage)
Known then as Cardiac Rehabilitation Exercise Physiologist / Clinical Exercise Physiologist (Medicare-covered CR era)
Known then as Exercise Physiologists (BLS SOC 29-1128, formal standalone occupation)
Known today as Exercise Physiologists (BLS SOC 29-1128, formal standalone occupation)
Projected to still be called Exercise Physiologists (BLS SOC 29-1128, formal standalone occupation)
Data from the May 2025 survey
US Employment
9K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$59,460
Est.

≈ $57,936 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1927

The Harvard Fatigue Laboratory opens in the basement of Morgan Hall at Harvard Business School, under the informal direction of D.B. Dill. Over the next 20 years it trains most of the next generation of US exercise scientists, producing foundational research on altitude physiology, heat adaptation, blood chemistry during maximal exercise, and the physiology of aging. When the laboratory closes in 1947, its alumni populate the physiology departments and exercise science programs that will eventually supply clinical cardiac rehabilitation with its workforce.

Beat · 1954

The American College of Sports Medicine is founded on April 22, 1954, at the Hotel Statler in New York City as part of an AAHPER afternoon program, with 11 founding members (7 physical educators, 1 woman, and 3 physicians). Its founding mission: to connect health problems with lifestyle choices, particularly physical inactivity. ACSM will go on to develop the certification infrastructure (ACSM-EP, ACSM-CEP, RCEP) that formally defines the clinical exercise physiology profession and sets the credential standards recognized by hospitals, insurers, and Medicare.

Beat · 1982

Medicare begins covering cardiac rehabilitation under the Social Security Act in 1982, providing the reimbursement foundation that enables hospitals to employ clinical exercise physiologists as a dedicated CR staff category. Before 1982, CR programs operated without a stable payment mechanism; the Medicare coverage decision transforms cardiac rehabilitation from a research-supported pilot program into a mainstream clinical service. The number of hospital-based CR programs expands substantially through the 1980s, and the clinical exercise physiologist becomes the primary provider of supervised exercise and behavior change counseling in these programs.

Beat · 2010

The 2010 Standard Occupational Classification revision introduces SOC 29-1128 as a new standalone occupation for Exercise Physiologists, separating them from adjacent categories (physical therapists, fitness trainers, health educators) for the first time in BLS survey history. The 2012 BLS OEWS is the first nationally representative employment count under the new code: 5,820 workers, with 54% in general medical and surgical hospitals. The formal recognition is significant: it signals that the clinical exercise physiology role has reached sufficient scale and distinctiveness to warrant its own occupational category in the federal statistical system.

Beat · 2020

The COVID-19 pandemic forces US cardiac rehabilitation programs to adopt telehealth delivery in March 2020 when in-person sessions become impossible. CMS issues waivers allowing Medicare-covered cardiac rehabilitation to be delivered via video; platforms like Carda Health launch to serve the virtual CR market. The pandemic-forced transition demonstrates that supervised exercise sessions via video with wearable monitoring are clinically viable -- a finding that permanently changes the delivery model for the profession. Virtual CR positions begin appearing in exercise physiologist job postings by mid-2020, a category that did not exist twelve months earlier.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace exercise physiologists? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+12.8%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 29-1128 (Exercise physiologists): 21.2 thousand jobs in 2025, projected 23.9 thousand in 2035, a change of +2.7 thousand (+12.8%). Matrix employment counts all jobs in the occupation, including self-employed workers (58.9% of this occupation in 2025). The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
34%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 29-1128.00 Exercise Physiologists. Shown: human-rated β = 0.34, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.28 and γ (all LLM-assisted) 0.4; GPT-4-rated β 0.26. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for exercise physiologists

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereDocument session data and generate progress reports, entering exercise session parameters (modality, intensity, duration, HR/BP response, symptoms), test results (CPET, 6MWT, strength), and patient-reported outcomes into MEDITECH or Epic, using AI-assisted documentation tools where available to auto-populate structured fields from session notes, and preparing periodic progress summaries for referring cardiologists and pulmonologists.

Document session data and generate progress reports, entering exercise session parameters (modality, intensity, duration, HR/BP response, symptoms), test results (CPET, 6MWT, strength), and patient-reported outcomes into MEDITECH or Epic, using AI-assisted documentation tools where available to auto-populate structured fields from session notes, and preparing periodic progress summaries for referring cardiologists and pulmonologists.[1],[7]

Where your edge is

Documentation is the highest AI-exposure task in clinical exercise physiology: CPET software already auto-generates structured reports, EHR AI scribes are entering cardiac rehab settings, and templated progress notes are increasingly auto-populated from structured session inputs. Your value in documentation shifts to clinical accuracy and physician communication: ensuring the CPET report narrative correctly characterizes the patient's functional limitations for the cardiologist, and that progress notes capture the nuance (symptoms, adherence barriers, medication changes) that structured fields miss.

AI is sitting alongside you hereReview AI-generated remote monitoring data from wearable cardiac sensors between supervised sessions, interpreting continuous heart rate, pulse oximetry, step counts, and AI-flagged arrhythmia alerts from patient wearables (Apple Watch, Polar, or clinic-prescribed chest patches), cross-referencing against each patient's prescribed exercise intensity targets and cardiac history, and deciding whether to contact the patient, adjust the next session prescription, or escalate to the supervising cardiologist.

Review AI-generated remote monitoring data from wearable cardiac sensors between supervised sessions, interpreting continuous heart rate, pulse oximetry, step counts, and AI-flagged arrhythmia alerts from patient wearables (Apple Watch, Polar, or clinic-prescribed chest patches), cross-referencing against each patient's prescribed exercise intensity targets and cardiac history, and deciding whether to contact the patient, adjust the next session prescription, or escalate to the supervising cardiologist.[5],[8]

Where your edge is

AI wearable monitoring transforms your between-session visibility from zero to continuous: you can now see if a patient walked at the prescribed intensity on non-supervised days, or if their Apple Watch flagged an AF episode overnight. The decision loop (what to do with the flag) remains yours: the ML identifies the signal, but you determine clinical significance in context of that specific patient's history, medications, and current program phase. Develop systematic triage habits for your remote monitoring queue so flags get reviewed daily and high-risk patients get proactive contact.

AI is sitting alongside you hereDevelop individualized exercise prescriptions for patients with chronic cardiovascular, pulmonary, or metabolic disease, integrating CPET-derived anaerobic threshold and peak VO2 data, physician medical clearance notes, patient goals, and current functional capacity assessments into a structured periodized program specifying modality, intensity (heart rate or Borg RPE targets), duration, frequency, and progression criteria.

Develop individualized exercise prescriptions for patients with chronic cardiovascular, pulmonary, or metabolic disease, integrating CPET-derived anaerobic threshold and peak VO2 data, physician medical clearance notes, patient goals, and current functional capacity assessments into a structured periodized program specifying modality, intensity (heart rate or Borg RPE targets), duration, frequency, and progression criteria.[1],[10]

Where your edge is

CPET-derived prescription data (VT1-anchored intensity, peak VO2 as functional capacity benchmark) is now automatically extracted and plotted by OMNIA and similar software: the algorithmic piece of prescription writing is increasingly templated. Your differentiation is the clinical reasoning layer: why this patient's anaerobic threshold-based prescription needs to be modified for their beta-blocker blunted heart rate response, or why a COPD patient's SpO2 at moderate intensity warrants supplemental O2 during exercise. No software substitutes for that integrative clinical judgment.

Where exercise physiologists go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Medical and Health Services Managers

Experienced clinical exercise physiologists who develop program management skills (running a cardiac or pulmonary rehabilitation department, managing staff, budgeting for CPET equipment and wearable monitoring platforms, coordinating physician coverage, and implementing quality metrics) are positioned for Cardiac Rehab Program Director, Director of Clinical Exercise, or healthcare administration roles. As hospital systems and virtual CR providers (Carda Health) scale their programs, they need managers who understand both the clinical and the technology dimensions. An MHA or MBA in Healthcare Management accelerates the transition.

What you'd add
  • · Healthcare management graduate credential: MHA, MBA (Healthcare Management), or MS in Health Services Administration
  • · Budget management: operating and capital budget ownership including CPET equipment lifecycle and wearable platform contracts
  • · Quality and accreditation: AACVPR program certification standards, CMS conditions of participation for cardiac rehab, HEDIS cardiac rehab utilization metrics
  • · Staff management: hiring and supervising CEPs, cardiac rehab nurses, and dietitians; AACVPR accreditation documentation
  • · Data analytics: extracting and presenting program outcome metrics (functional capacity gains, readmission rates, completion rates) to hospital leadership
What it takesSome new skills to pick up
Tools of the era

How has the work of exercise physiologists changed since 1927?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Spirometers, Douglas bags, and chemical gas analysis (laboratory era)

    The founding generation of exercise physiologists worked with spirometers to measure lung volumes, Douglas bags (a large gas-collection bag invented by C.G. Douglas in 1911) to capture expired air during exercise, and Haldane gas analyzers to determine oxygen and carbon dioxide concentrations by chemical absorption. Measuring someone's maximal oxygen uptake -- what we now call VO2max -- required collecting a bag of expired gas during maximal exertion, then spending many minutes analyzing it by hand with acid and alkali absorption pipettes. The entire workflow was precise, time-consuming, and required deep chemistry knowledge. These tools defined what questions exercise physiologists could ask: those that could be answered by measuring gas exchange at the mouth and blood chemistry at rest and exercise. Equipment was custom-built, expensive, and confined to research laboratories.

    Effect on the work

    The complexity and cost of early gas-analysis equipment kept exercise physiology confined to well-funded academic research programs through the 1950s and 1960s. Only a university or major hospital could afford the instrumentation; clinical exercise testing did not scale until automated systems replaced the Douglas bag and Haldane analyzer.

  • Electrocardiographic exercise stress testing (Bruce Protocol 1963, treadmill-based clinical testing)

    In 1963, Robert A. Bruce at the University of Washington published the exercise test protocol that still bears his name: a treadmill-based graded exercise test with standardized stages of increasing speed and incline, accompanied by continuous 12-lead ECG monitoring. The Bruce Protocol transformed exercise testing from a research tool into a clinical diagnostic instrument. For exercise physiologists, the stress test became the defining clinical procedure: preparing the patient with electrode placement, calibrating the treadmill, supervising the incremental protocol, monitoring the ECG in real time for ischemic changes or arrhythmias, and determining when to stop the test. The combination of the Bruce Protocol and advances in ECG monitoring technology created the clinical role that exercise physiologists would fill in cardiac rehabilitation programs for the next fifty years.

    Effect on the work

    The adoption of structured exercise stress testing in clinical cardiology during the 1960s and 1970s created the specific demand for trained exercise physiologists in hospitals for the first time. Until the stress test became a standard clinical tool, there was no clinical workflow that specifically required an exercise physiology credential.

  • Metabolic carts and automated CPET systems (SensorMedics, MedGraphics, early COSMED)

    The automated metabolic cart -- a system that analyzes expired gas breath-by-breath using electrochemical or infrared sensors rather than manual chemical analysis -- arrived in clinical and research settings in the late 1970s and early 1980s. SensorMedics, Medical Graphics Corporation (MedGraphics), and later COSMED built clinical CPET platforms that measured VO2, VCO2, ventilatory equivalents, and respiratory exchange ratio in real time, displayed results on a screen during the test, and printed reports automatically. For exercise physiologists, the metabolic cart replaced many minutes of post-test chemical analysis with a digital printout. The exercise physiologist's role shifted from gas analyst to clinical interpreter: reading the nine-panel CPET plot, identifying the ventilatory anaerobic threshold, classifying exercise limitation (cardiac vs. pulmonary vs. deconditioning), and translating the results into an exercise prescription. This required more clinical knowledge, not less.

    Effect on the work

    Automated CPET systems dramatically expanded the volume of exercise tests a single exercise physiologist could conduct and interpret. The bottleneck shifted from data collection (now automated) to clinical reasoning (still human). This productivity gain enabled hospitals to scale their cardiac and pulmonary rehabilitation programs through the 1990s without proportionally expanding their exercise physiology staff.

  • Electronic health records and MEDITECH / Epic integration

    The adoption of electronic health records in hospital systems through the late 1990s and 2000s (MEDITECH, Epic, Cerner) changed the documentation workflow for clinical exercise physiologists in cardiac and pulmonary rehabilitation. Session data, CPET results, functional test findings, and progress notes moved from paper flow sheets into structured EHR fields requiring physician co-signature. Exercise physiologists gained visibility into patients' full medical records for the first time, enabling better-informed exercise prescriptions that accounted for medications (beta-blockers, anticoagulants, diuretics), recent lab values, and comorbidities. They also became responsible for meeting CMS documentation requirements for Medicare-covered cardiac rehabilitation, which specified session content, intensity documentation, and progress monitoring criteria. EHR fluency became a core competency for hospital-based exercise physiologists.

  • Wearable cardiac monitors and consumer-grade biosensors (Polar, Garmin, Apple Watch Series 4+)

    Consumer wearable devices -- fitness trackers, GPS heart rate monitors, and eventually medical-grade smartwatches -- began changing the information environment for exercise physiologists around 2015. The Apple Watch Series 4, cleared by the FDA in 2018 for its ECG app and irregular rhythm notifications, was the threshold moment: a device worn by millions of people could now detect atrial fibrillation with clinically meaningful sensitivity. For exercise physiologists working in cardiac rehabilitation, wearables opened a window into patient activity between supervised sessions that had previously been entirely opaque. Step counts, heart rate trends, sleep data, and (for approved devices) single-lead ECG readings gave clinicians objective data for behavior change counseling conversations. The transition was not frictionless: consumer wearables were not designed for clinical workflow integration, and exercise physiologists had to develop informal protocols for reviewing and acting on wearable data that clinics had not systematically organized.

  • AI-enabled virtual cardiac rehabilitation (Carda Health, telehealth video, ML adherence prediction)

    The COVID-19 pandemic forced US cardiac rehabilitation programs to pivot to telehealth delivery in 2020, creating the conditions for the first national virtual-only cardiac rehabilitation platforms. Carda Health, founded in 2020, became the first national provider delivering integrated cardiopulmonary rehabilitation entirely via video sessions, with real-time wearable vital sign monitoring and AI-driven patient engagement. For exercise physiologists, this represented the most significant structural change in the role since Medicare coverage in 1982: a remote CEP can now supervise Phase II cardiac rehabilitation sessions via live video while reviewing real-time pulse oximetry and heart rate data, manage an AI-driven monitoring queue of between-session wearable data, and receive ML-generated adherence risk scores identifying patients likely to drop out. Apple Watch convolutional neural network algorithms detect atrial fibrillation with 97.5% episode sensitivity. ML models predict patient adherence to CR programs with 80% accuracy. The exercise physiologist's daily work now involves reviewing AI-generated flags and making clinical decisions about what to act on -- a shift from purely procedural supervision to AI-augmented remote case management. CMS issued updated guidelines in 2020 allowing telehealth delivery of cardiac rehabilitation under Medicare, normalizing the virtual format.

    Effect on the work

    Virtual cardiac rehabilitation platforms with AI-enabled monitoring expand the patient panel a single exercise physiologist can manage: a remote CEP reviewing daily wearable data for many patients simultaneously represents a different scale of practice than supervising several patients per day in a traditional outpatient program. Whether this leads to net job creation (serving more patients who previously could not access CR) or productivity substitution (fewer CEPs per patient treated) is an open empirical question as of 2026.

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Exercise Physiologists employment and pay by year

On record since1927
Latest US employment8,560 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$59,460 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+12.8% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 20 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
192720n/aEst., Harvard Fatigue Laboratory Researched contextReport
1960500n/aEst., American College of Sports Medicine Researched contextReport
19823,000$22,000Est., Historical Context of Cardiac… Researched contextReport
20008,000n/aEst., American College of Sports Medicine Researched contextReport
201016,170$47,950BLS OEWS May 2010 Official statisticReport
201115,720$49,120BLS OEWS May 2011 Official statisticReport
20125,820$44,770BLS OEWS May 2012 Official statisticReport
20136,010$46,020BLS OEWS May 2013 Official statisticReport
20146,660$46,270BLS OEWS May 2014 Official statisticReport
20156,620$47,010BLS OEWS May 2015 Official statisticReport
20166,880$47,340BLS OEWS May 2016 Official statisticReport
20176,300$49,090BLS OEWS May 2017 Official statisticReport
20186,740$49,270BLS OEWS May 2018 Official statisticReport
20197,280$49,170BLS OEWS May 2019 Official statisticReport
20207,330$50,280BLS OEWS May 2020 Official statisticReport
20216,860$47,940BLS OEWS May 2021 Official statisticReport
20226,580$51,350BLS OEWS May 2022 Official statisticReport
20238,060$54,860BLS OEWS May 2023 Official statisticReport
20248,110$58,160BLS OEWS May 2024 (employment) Official statisticBLS OEWS May 2024 (pay) Official statisticReport
20258,560$59,460BLS OEWS May 2025 Official statisticReport
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