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Pulse watch

A pulse watch, also known as a pulsometer or pulsograph, is a specialized timepiece featuring a graduated scale on its dial or that allows for the quick and approximate of a person's by timing a fixed number of beats, typically or 30. The origins of the pulse watch trace back to 1707, when English physician Sir John Floyer collaborated with watchmaker Samuel Watson to develop the first Physician's Pulse Watch, a with a graduated dial designed to calculate rates more efficiently than manual counting. This innovation addressed the need for precise timing in medical practice, as Floyer emphasized the importance of monitoring variations in his treatise The Physician's Pulse Watch. By the early , with the advent of wrist s, Swiss manufacturers like (from 1913) and Breitling (from 1915) adapted the pulsometer scale for wearable formats, making it a staple for doctors during house calls and in hospitals. Notable early models include the 1928 Prince, equipped with a dedicated seconds dial for timing, and the Universal Genève Medico-Compax, which integrated the scale directly into the chronograph layout. In operation, a user starts the while feeling the patient's , counts the specified number of beats (often 30 for standard scales), and stops the timer; the second hand then aligns with the scale to display the in beats per minute without further calculation—for instance, if the hand stops at the 80 mark after 30 beats, the rate is approximately 80 . Variations exist, such as scales calibrated for 15 beats to expedite measurements in urgent scenarios, and some models use the main seconds hand instead of a for simpler designs. While pulse watches were essential tools for medical professionals until the mid-20th century, they have since been largely replaced by electronic monitors and smartwatches with optical sensors; however, luxury brands like , , and modern revivals from Delma continue to produce them as functional homages to horological history.

History

Early Inventions

A pulse watch is a specialized timepiece designed to measure by timing pulsations from the , distinguishing it from conventional watches that solely track time. The earliest known pulse watch emerged in 1707, commissioned by English physician Sir John Floyer from watchmaker Samuel to facilitate precise pulse counting for . This device featured a seconds hand and a graduated scale allowing the user to count 15 beats starting from the 12 o'clock position and read the directly from the dial upon reaching the 15th beat, enabling quick assessments without complex calculations. In the , advancements in technology adapted these principles for more efficient , with Louis Moinet's 1816 invention of the compteur de tierces—a high-frequency capable of tracking elapsed time to 1/60th of a second—providing a foundational tool for timing medical observations, though initially developed for astronomical use. By the late 1800s, pocket like a Breguet circa 1880 model incorporated dedicated pulsometer scales, often graduated for 60 beats, where the user would start the on the first and stop it after a set number of beats to read the rate directly from the scale. In the early , wristwatches with pulsometer bezels became available, with manufacturers like introducing them from 1913 and Breitling from 1915; these typically used a 15-beat or 30-beat scale, where the seconds hand's position after counting the beats indicated beats per minute via proportional markings, streamlining . Early 20th-century innovations extended these mechanical designs to specialized fields, including and , as exemplified by ' 1920s pulsometer chronographs, which used single-button operation and 30-beat scales for rapid checks by personnel, including those supporting pilots. These analog instruments laid the groundwork for later electronic developments in monitoring.

Modern Evolution

The modern evolution of pulse watches began in 1977 with the invention of the world's first wireless by Finnish innovator Seppo Säynäjäkangas, founder of , which utilized ECG electrodes in a chest strap to transmit digital signals to a wrist receiver for real-time monitoring during . This marked the shift from mechanical analog devices to electronic digital systems, enabling precise, data-driven tracking for athletes and laying the foundation for wearable fitness technology. During the and , efforts focused on transitioning to wrist-based designs, with early optical prototypes emerging, such as Seiko's 1983 Pulsemeter, a digital that incorporated a with a wired chest band or fingertip contact for transmission to the wrist unit. These innovations evolved from wired ECG systems to more convenient optical methods using light-based detection, though widespread adoption was limited by accuracy challenges and bulkiness until wireless protocols improved in the late . The 2000s saw integration into dedicated fitness watches, exemplified by Garmin's Forerunner 201 in 2003, which supported external monitors via wireless chest straps to track pace, distance, and heart rate data for runners. Early smartwatches followed, with the Pebble 2 in 2016 introducing built-in optical tracking alongside notifications and fitness metrics, broadening appeal beyond elite athletes. The 2010s and early 2020s witnessed explosive growth, driven by photoplethysmography (PPG) sensors in consumer devices; Apple introduced PPG-based heart rate monitoring in the Apple Watch in 2015, enabling continuous wrist-based tracking without straps. Fitbit pioneered automatic continuous optical monitoring with PurePulse technology in 2014, integrated into bands like the Charge HR. By 2024, advancements included FDA clearance for Samsung Galaxy Watch's atrial fibrillation detection via PPG and ECG, allowing irregular rhythm notifications for users over 22. The global wearable heart rate monitor market reached approximately $15 billion by 2025, fueled by health awareness and smartphone integration.

Technology and Operation

While traditional pulse watches rely on mechanical chronographs with graduated scales for manual pulse timing, modern electronic pulse watches—often integrated into smartwatches and fitness trackers—employ advanced sensors and algorithms for automated detection.

Sensing Methods

Photoplethysmography (PPG) is the most widely adopted sensing method in modern pulse watches, utilizing light-emitting diodes (LEDs), typically green, and photodiodes to detect changes in in the microvascular of the . Green is particularly effective because it is absorbed by in the blood, allowing the to capture pulsatile variations in transmission or reflection as the heart beats cause arterial to expand and contract. This optical technique produces a whose peaks correspond to heartbeats, from which the pulse rate can be derived using the formula: \text{BPM} = \frac{60}{\text{average inter-beat interval (in seconds)}} where the inter-beat interval is the time between consecutive peaks. PPG sensors in modern electronic pulse watches typically operate at sampling rates around 100 Hz to capture the pulsatile signal adequately, though optimal rates for monitoring can range from 21 to 64 Hz depending on the device and activity level. To enhance accuracy during motion, many modern PPG implementations incorporate multi-wavelength LEDs, such as combinations of , , and , which help mitigate motion artifacts by providing multiple signal channels for differential . Electrocardiography (ECG)-based sensing offers an alternative hardware approach in some modern electronic es, employing single-lead through integrated into the wrist device to detect the heart's electrical activity. In devices like the Series 4 and later models, one is located on the back of the watch in contact with , while the other is at the digital crown, forming a circuit when the user touches it with a finger to record the electrical potential difference generated by cardiac . This method captures the and other features of the ECG waveform directly from bioelectric signals propagating through the body. Less common in commercial modern electronic pulse watches are methods like bioimpedance analysis, which measures changes in electrical resistance across body tissues due to fluctuations during the , and (BCG), which detects subtle mechanical motions or vibrations induced by heartbeats using accelerometers or force sensors. Bioimpedance typically involves applying a low-amplitude via electrodes and monitoring impedance variations, offering a non-optical means to infer pulse waveforms. BCG, meanwhile, captures recoil forces from blood ejection, though its integration into wrist-worn devices remains experimental and less prevalent compared to PPG or ECG.

Data Processing

The data processing in modern electronic pulse watches involves algorithms that transform raw signals, primarily from photoplethysmography (PPG), into meaningful metrics such as beats per minute and (HRV). These processes occur on-device or via connected systems to enable real-time analysis while minimizing computational load. Signal filtering is a foundational step to isolate the pulsatile component of the PPG from noise sources like motion artifacts. Bandpass filters, typically set between 0.5 and 4 Hz to capture adult heart rates ranging from 30 to 240 beats per minute, attenuate low-frequency baseline wander and high-frequency interference. This preprocessing enhances signal quality before further analysis. Peak detection algorithms then identify individual heartbeat peaks within the filtered signal to compute interbeat intervals. Techniques such as detect periodic patterns in the waveform, while transforms analyze the frequency spectrum to pinpoint the dominant heartbeat frequency. From these intervals, HRV metrics are derived; for instance, the standard deviation of normal-to-normal (NN) intervals, denoted as SDNN, quantifies overall variability as \text{SDNN} = \sqrt{\frac{1}{N} \sum_{i=1}^{N} (NN_i - \overline{NN})^2 }, where NN_i are the NN intervals and \overline{NN} is their . In devices from the , enhancements improve robustness, particularly in dynamic conditions. Adaptive filters dynamically adjust to signal variations, and Kalman filters provide real-time state estimation for correcting artifacts by fusing PPG data with inputs. models, including neural networks, enable , such as identifying irregular rhythms indicative of through in PPG waveforms. Processed metrics are transmitted via (BLE) protocols to companion smartphone applications for logging, visualization, and long-term storage. This low-power standard ensures efficient, intermittent data syncing without draining device batteries.

Types of Devices

Wrist-Based Monitors

Wrist-based monitors are dedicated wearable devices positioned on the wrist, engineered specifically for continuous tracking to support athletic performance and exercise monitoring. These devices, while successors to traditional watches, employ optical photoplethysmography (PPG) sensors embedded in the watch case or to detect flow changes via , providing real-time beats per minute () data without the need for external attachments. Unlike multifunctional smartwatches, they prioritize simplicity and reliability for focused use during physical activities such as running or . Design features of wrist-based monitors emphasize durability and comfort for extended wear, including lightweight casings constructed from or materials, adjustable or straps for secure fit across various wrist sizes, and dedicated LCD or displays optimized for quick BPM readouts even in motion. For instance, the Polar Vantage series incorporates a slim, lightweight casing weighing about 57 grams with a adjustable strap and a high-contrast that prominently shows zones and current BPM values. Similarly, models feature casings under 50 grams, flexible straps with multiple adjustment holes, and straightforward digital screens for immediate visibility during workouts. These monitors operate independently with robust standalone functionality, offering battery life up to 7 days in standard mode and no reliance on pairing for core tracking, allowing athletes to focus on capture during exercise sessions. The Polar Vantage V3, for example, delivers up to 10 days in mode, supporting uninterrupted without external devices, though continuous optical tracking reduces this duration. variants provide comparable longevity through replaceable coin cell , enabling timing and alerts solely from the wrist unit. Early examples trace back to the series in the 1990s, which laid the groundwork for wrist-based tracking with basic digital interfaces that later integrated heart rate capabilities in subsequent iterations. Contemporary models, such as the 2025 Polar Vantage lineup, enhance this legacy with ANT+ connectivity for broadcasting data to compatible gym equipment or bikes, maintaining a dedicated focus on exercise-oriented monitoring. The portability of these devices—compact form factors under 60 grams—and their intuitive one-button access to heart rate functions make them particularly advantageous for athletes, facilitating seamless integration into training routines without added bulk or complexity.

Mechanical Pulsometers

Traditional pulse watches, or mechanical pulsometers, are timepieces featuring a graduated scale on the dial or for measuring by manually timing a fixed number of pulse beats, typically 15 or 30. These originated as watches in the early and evolved into wrist-based models by the early . Early wrist examples include the pulsometer from 1913 and Breitling's 1915 model, designed for medical professionals. The 1928 Prince featured a dedicated seconds dial for timing, while the Universal Genève Medico-Compax integrated the scale into the layout. These devices required the user to start the , count beats while palpating the , and stop at the specified count, with the second hand indicating directly on the scale. Modern mechanical pulsometers continue as luxury homages, such as Patek Philippe's Reference 5170 with a 15-beat , Omega's Seamaster with pulsometer , and Delma's revivals incorporating the feature for functional appeal. These maintain the analog precision and horological craftsmanship, appealing to collectors and professionals valuing traditional methods over electronic alternatives.

Advanced Integrated Systems

Advanced integrated systems represent evolutions of pulse monitoring in multifunctional smartwatches and devices that combine tracking—often via optical sensors—with other features, though distinct from traditional pulsometer scales. These systems utilize wrist-based optical sensors to track alongside (GPS) for location-based activity mapping, smartphone notifications for real-time alerts, and ecosystem integrations such as Wear OS or Apple's for synchronized data across devices. This integration enables users to receive comprehensive health insights without compromising on smart functionalities like app access and voice assistance, distinguishing them from simpler trackers or mechanical pulse watches. Prominent examples include the series, which from its 2022 launch has incorporated for blood oxygen levels alongside monitoring, with 2025 updates via 11.6.1 restoring full blood oxygen functionality for U.S. users through redesigned collection. Similarly, the Vivosmart 5 fitness tracker integrates tracking with notifications and basic ecosystem connectivity via the Garmin Connect app, while the GT series, such as the GT 5 Pro, combines monitoring with SpO2 measurements, GPS navigation, and integration for extended feature sets. These devices exemplify how is fused with multi- arrays to broader tracking. Power management in these systems balances continuous monitoring needs with battery efficiency, employing always-on pulse detection for real-time alerts versus on-demand sampling to conserve energy. AI-optimized algorithms adjust sampling rates based on activity levels, extending life to 24-48 hours in models like the and , where adaptive acquisition reduces power draw during low-intensity periods. In the market landscape, hybrids dominate wrist-worn wearables, reflecting their appeal through integrated and smart features over basic bands. This dominance underscores the shift toward devices that prioritize holistic user experiences in health and connectivity.

Accuracy and Reliability

Influencing Factors

Motion artifacts represent a primary impacting the accuracy of watches, which typically rely on photoplethysmography (PPG) to detect changes through light absorption. Arm movements during daily activities or exercise introduce signal noise by shifting the relative to the skin, often manifesting as false or missing beats that distort calculations. While accelerometers in modern devices help mitigate these artifacts by filtering motion-correlated noise, accuracy still declines during high-intensity exercise, with mean absolute errors (MAE) of up to 14 (approximately 10-15% at typical heart rates) due to persistent signal interference. Skin tone and device fit further influence PPG signal quality, as darker skin tones absorb more , thereby reducing the () and potentially leading to underestimated heart rates. This effect arises because higher concentrations in darker reflect less incident back to the , weakening the pulsatile component of the PPG . Similarly, a loose wrist strap exacerbates errors by creating gaps between the and , which diminish contact and introduce additional motion-induced ; studies indicate that suboptimal fit can significantly increase measurement errors compared to a snug placement. Physiological states such as arrhythmias and cold temperatures also alter pulse measurement reliability by affecting peripheral and signal regularity. Arrhythmias, including , disrupt the rhythmic blood flow detected by PPG, leading to irregular pulse waveforms that challenge accurate beat-to-beat interval estimation and can result in erroneous average heart rates. Cold temperatures induce , reducing blood volume in peripheral tissues and thereby attenuating the PPG signal , which compromises detection in low-perfusion conditions. Device-specific factors, including sensor quality and , contribute to variability in pulse watch performance, particularly in budget models where lower-grade photodiodes and less sophisticated algorithms yield higher resting variance of approximately ±5 beats per minute () relative to reference standards. Premium devices often incorporate better protocols and multi-wavelength LEDs to enhance signal stability, minimizing such discrepancies under controlled conditions.

Validation Studies

Validation studies for pulse watches primarily evaluate their accuracy against (ECG), the gold standard for and rhythm measurement, often employing Bland-Altman analyses to quantify agreement through metrics like (MAE). For instance, assessments of the have demonstrated MAEs ranging from 2 to 5 beats per minute (BPM) at rest, indicating strong concordance with ECG under controlled conditions. These comparisons highlight the reliability of photoplethysmography-based sensors in static scenarios but underscore the need for rigorous benchmarking across activities. Key clinical trials have further validated pulse watch capabilities for detecting arrhythmias. Apple's internal validation study for the ECG app on the Apple Watch Series 4 reported a sensitivity of 98.3% and specificity of 99.6% for (AFib) detection compared to a clinical 12-lead ECG reference. Complementing this, the 2019 Apple Heart Study, published in the Journal of Medicine, assessed irregular pulse notifications in over 400,000 participants, confirming high positive predictive value (84%) for AFib in a subset validated with ECG patches, though full was not directly measured in the large cohort. For exercise monitoring, recent validations of devices, such as a 2022 comparative analysis, showed strong correlation (r=0.95) with ECG during dynamic conditions, supporting their utility in fitness contexts. Regulatory bodies have endorsed certain pulse watch features based on these validations. The U.S. (FDA) granted Class II clearance to the Apple Watch's Irregular Rhythm Notification Feature in 2018 for alerting users to potential AFib, classifying it as a moderate-risk device with demonstrated safety and effectiveness. Similarly, the ECG app received FDA clearance under the same pathway. For components in wearables, compliance with ISO 80601-2-61:2017 ensures accuracy within specified limits (e.g., error ≤3% for SpO2), as verified in studies of devices like finger-worn and wrist-based oximeters. Despite these advancements, validation studies reveal limitations in diverse populations. Research indicates that pulse watches are understudied in individuals from varied ethnic backgrounds, with photoplethysmography sensors showing reduced accuracy—up to 20% higher error rates—in darker tones due to light absorption differences. Reviews indicate elevated errors of 10-20% during high-intensity activities due to motion artifacts, though overall trends remain reliable for general use. Motion remains a common error source in dynamic settings, as briefly evidenced across multiple device validations. As of 2025, studies continue to show greater errors in darker tones during moderate-to-high intensity (mean error up to 7.6 at 40-60% HRR), though overall skin tone effects remain inconclusive.

Applications

Fitness and Wellness

Pulse watches play a key role in and by enabling users to monitor in during exercise, allowing them to target specific training zones for optimized performance and utilization. zones are typically divided based on percentages of maximum , with the fat-burning zone often falling between 60% and 70% of maximum , where the body relies more heavily on as an source compared to higher- efforts. For example, during moderate aerobic activities like , users can maintain this zone to promote and , with pulse watches providing vibrational or visual alerts to stay within the desired and adjust accordingly. Key features of pulse watches for fitness include estimation derived from data and recovery tracking through (HRV). Calorie burn is approximated using formulas that incorporate , age, weight, and gender, providing users with an estimate of expenditure during workouts by accounting for individual physiological responses. This method, while approximate, helps track progress in activities like or weight training. Additionally, HRV measurements, captured during rest or , indicate balance and recovery status; higher HRV values suggest better adaptation to training stress, guiding users to adjust workout loads to prevent . User adoption of pulse watches in fitness settings has surged, with ranked as the top global fitness trend in 2025 surveys, reflecting widespread reliance among gym-goers for motivation and performance insights. These devices often integrate seamlessly with apps like , automatically syncing data from workouts to enable detailed analysis of routes, efforts, and social sharing within fitness communities. In wellness applications, pulse watches track resting heart rate trends to detect levels, as elevations in baseline over time can signal accumulated physiological from daily life or intense training. By monitoring overnight or morning readings, users receive insights into needs, prompting adjustments like additional rest or practices to maintain overall .

Healthcare Monitoring

Historically, mechanical pulse watches were essential for physicians to quickly assess patient s during examinations. Pulse watches play a significant role in clinical diagnostics through arrhythmia detection capabilities, where built-in algorithms analyze photoplethysmography (PPG) signals to flag irregular heart rhythms such as (AFib). In the Apple Heart Study, involving 419,297 participants, an irregular pulse notification feature demonstrated a positive predictive value of 84% for identifying AFib, with 0.52% of users receiving alerts that prompted further evaluation via ECG patches, confirming AFib in 34% of cases among those tested. These notifications have facilitated early interventions, as 57% of notified participants contacted healthcare providers within 90 days, potentially averting complications like through timely medical follow-up, including emergency room visits for confirmation and treatment. In , pulse watches integrate with platforms to track for managing chronic conditions such as , enabling proactive adjustments to plans. A of high-risk postdischarge patients using home telemonitoring devices, including those measuring and , reported a 57.8% reduction in hospitalizations and a 19.4% decrease in hospital days at six months, attributed to early detection of physiological deviations. Similarly, remote monitoring programs for patients, often comorbid with , have achieved up to 50% reductions in 30-day readmissions by continuously monitoring trends and alerting providers to anomalies. These systems ensure and compliance with the Health Insurance Portability and Accountability Act (HIPAA), as wearable-derived health information is transmitted via encrypted channels to authorized clinicians. Continuous heart rate tracking via pulse watches supports monitoring in post-operative recovery and , providing real-time data to detect or that could signal infections or . In post-surgical settings, wearable sensors have been shown to identify early physiological changes, such as elevated s, allowing for remote oversight that reduces the need for frequent in-person visits. For elderly patients, these devices facilitate aging-in-place programs by monitoring alongside activity levels, with HIPAA-compliant platforms ensuring remains secure during transmission to caregivers. Validation studies confirm high accuracy for such measurements in clinical contexts, supporting their reliability for medical decision-making. Case studies from the highlight pulse watches' utility in early disease detection through elevated resting s. A of wearable sensors from 2020-2022 found that devices like the and detected changes in , identifying up to 88% of infections up to four days before symptom onset in presymptomatic individuals. These findings, drawn from studies involving thousands of participants, underscored the potential for population-level , where sustained elevations in resting served as a non-invasive for onset during the 2020-2022 outbreak waves.

Future Developments

Technological Innovations

Advancements in multi-modal sensor technologies are revolutionizing pulse watches by combining traditional photoplethysmography (PPG) with radar and ultrasound for non-contact heart rate monitoring, addressing current PPG limitations such as motion artifacts that can degrade accuracy during physical activity. Google's 2025 research on consumer ultra-wideband (UWB) radar, integrated into mobile devices, enables contactless heart rate detection using deep learning models, achieving a mean absolute error of 4.1 beats per minute and a mean absolute percentage error of 6.3%, which meets Consumer Technology Association standards for wearable monitors. Complementary ultrasound-based systems, such as multi-channel prototypes, capture subtle vibrations for vital sign tracking without skin contact, with ongoing multi-modal fusions of radar, acoustic, and thermal sensors showing promise for robust performance in dynamic environments. By 2030, these integrations are projected to enable seamless, interference-free monitoring in everyday wearables. AI enhancements in pulse watches are introducing sophisticated predictive analytics for health risk assessment, leveraging machine learning to analyze continuous data streams for early intervention. Research from the SCAI 2025 Scientific Sessions demonstrates that AI-paired wearables can detect cardiovascular events up to one hour in advance, with over 90% sensitivity for atrial fibrillation detection comparable to hospital-grade equipment. Similarly, transformer-based AI models processing heart rate and activity data from devices like Fitbit have achieved 91% accuracy in predicting hospitalization risks, enabling proactive alerts for cardiac decompensation. These capabilities, expected to mature in 2026 consumer models, prioritize pattern recognition from multi-source inputs to forecast events like arrhythmias with high specificity, reducing false positives through refined algorithms. Battery and miniaturization innovations are extending operational longevity and improving user comfort in pulse watches. Solid-state batteries, such as Samsung's oxide-based variants with 200 watt-hours per liter , are set for in 2026, potentially delivering multi-week life under moderate usage while enhancing safety and flexibility for slimmer designs. Parallel developments in flexible displays, including curved panels, allow devices to conform ergonomically to the , reducing bulk and improving fit for prolonged wear without compromising visibility or durability. These advancements facilitate smaller form factors that maintain precision, with prototypes already demonstrating bendable substrates resilient to daily strains. Integration trends are fostering seamless connectivity between pulse watches, glasses, and implants to enable holistic monitoring ecosystems. -powered smart glasses are incorporating biosensors for real-time vital tracking, syncing with wrist devices to aggregate data on , oxygenation, and activity for comprehensive profiles. Implantable BioMEMS technologies, such as sensors for continuous glucose and cardiac monitoring, are advancing with wearables via low-power networks, allowing unified dashboards for multi-device insights. By 2030, these mergers will support predictive health platforms that correlate external and internal metrics, optimizing interventions through shared .

Regulatory and Ethical Considerations

Pulse watches, when marketed with medical claims such as diagnosing arrhythmias or monitoring cardiovascular conditions, are subject to stringent regulatory oversight by bodies like the U.S. (FDA) and the European Union's Medical Device Regulation (MDR). Under FDA guidelines, devices making diagnostic or therapeutic claims must undergo premarket clearance or approval, classifying them as Class II medical devices requiring 510(k) submission to demonstrate substantial equivalence to predicate devices. Similarly, the EU MDR (Regulation 2017/745) mandates for wearables intended for medical purposes, categorizing pulse watches as Class IIa or higher based on risk, with requirements for clinical evaluation, post-market surveillance, and conformity assessment by notified bodies. In , both FDA and EU regulators updated frameworks to emphasize cybersecurity, mandating secure data transmission protocols in premarket submissions to mitigate risks from connected devices, as outlined in FDA's final guidance on cybersecurity for medical devices. Privacy concerns surrounding pulse watches center on the handling of sensitive (HR) data, which qualifies as personal health information under regulations like the EU's (GDPR). Manufacturers must ensure GDPR compliance through explicit user consent for data collection and sharing, data minimization principles, and robust encryption to protect HR metrics transmitted to apps or cloud services. Non-compliance can result in fines up to 4% of global annual turnover. Risks of are amplified in connected ecosystems; for instance, a 2023 at Zoll Medical Corporation exposed of over 1 million users of their wearable cardioverter defibrillators, highlighting vulnerabilities in device-app integrations that could extend to pulse monitoring wearables. Ethical challenges include the potential for over-reliance on pulse watches, which may exacerbate anxiety or —a condition where constant monitoring of HR fluctuations leads users to misinterpret normal variations as serious issues, prompting unnecessary consultations. Studies indicate this effect is particularly pronounced in individuals predisposed to anxiety, with wearable alerts sometimes amplifying perceived symptoms without clinical context. Additionally, issues persist, as access to pulse watches remains limited for low-income groups due to high costs (often $100–$500 per device) and lack of coverage, widening health disparities; for example, ownership rates drop to about 12% among households earning below $30,000 annually compared to over 50% in higher-income brackets. Brief clinical validation studies underscore the need for diverse participant pools to address these biases, ensuring reliable HR readings across demographics. Looking ahead, proposed policies for 2026 aim to regulate AI-driven diagnostics in pulse watches more rigorously to prevent misdiagnosis. The FDA's 2026 guidance agenda includes lifecycle management for -enabled devices, requiring in algorithms and to ensure accurate HR-based predictions. In the , the AI Act's 2026 timeline for high-risk systems will impose conformity assessments on AI features in wearables, mandating human oversight and risk management plans to safeguard against erroneous health alerts. These standards build on existing validation needs to foster safer integration of in consumer health monitoring.

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