Suunto Blog

Find the coordinates. Start the race.  For 90 years Suunto has been creating tools for people who explore the world beyond the ordinary. To celebrate this milestone, we are inviting adventurers everywhere to take part in a global challenge. 
 Throughout the anniversary year our elite athletes will hide special Suunto chests in environments that represent their natural playground – from alpine mountains and northern wilderness to deep forests, open water, and vibrant city landscapes.  When a chest is hidden, the coordinates are released to the world. From that moment the race begins.  Anyone can join the challenge. 

The mission is simple: reach the location first. The first person to physically arrive at the chest wins the prize inside, while the next explorers to reach the location will receive runners‑up rewards. Every challenge will take place somewhere different. 
Some locations may be remote. Some might be closer than you think. But every one of them will invite you to step outside, explore new terrain and follow the coordinates to adventure. The Suunto 90 Challenge is our way of celebrating nine decades of exploration – by inspiring people around the world to get outside and discover what adventure means to them.   Sign up for coordinates How the challenge works: 1. Sign up below: Subscribe to Suunto newsletter to be the first to hear when new coordinates are released. 2. Get the coordinates: When a Suunto athlete drops a chest somewhere in the world, we will release the coordinates in our newsletter and @suunto Instagram – and the race begins! 3. Start the race: From that moment anyone can attempt to reach the location. Plan your route, prepare your gear and start moving. 4. Find the chest: The first explorer to reach the chest wins the prize inside. The next explorers will receive runners-up rewards.  

Last week, Suunto users around the world came together for the Suunto Commuting Day in an effort to do good for the planet. Here’s a snapshot of what the global community achieved! Small, everyday choices are the beginning of change. One single commute may not seem like much, but over time, it all adds up. And when we look at the entire Suunto community, we can see that together we can make a bigger impact! The combined CO₂e savings for the participants on Thursday, October 24 were over 65,000 kg. This collective effort shows that even small changes in our daily routines can have a real impact. 65,000 kg of CO₂e is equal to about 260 one-way flights from Paris to Berlin, where each passenger's emissions are around 0.25 metric tons for the 1.5-hour trip. It is also similar to the CO₂ absorbed by around 1,300 trees over ten years (based on Tree-Nation’s Eden Reforestation Projects in Mozambique). 65,000 kg is also equal to the emissions of 5,500 Finland-made Suunto Ocean watches generate during their whole lifespan. Half on bikes, half on foot Our data revealed that 49% of participants chose to cycle, 31% to run, and 20% to walk their commutes — each step and pedal turn contributing to both personal health benefits and a greener future. Whether on wheels, on foot, or even other creative methods, our Suunto users took meaningful action to reduce their carbon footprint. Distances covered and time invested Cyclists typically commuted around 7.9 km per trip, spending 28 minutes on average. Runners tackled 6.1 km per commute, taking 40 minutes on average. Walkers covered 2.7 km on average, enjoying 35 minutes outdoors. The bike commute distances are distributed quite evenly over different distances: roughly a third is less than 5 km, a third is between 5–10 km, and a third is over 10 km. The longest commuting rides last Thursday were over 100 km. Top commuting champions by country Our Swiss users led in cycling distances with an impressive 10.3 km being the most typical commuting distance, while runners in China topped the charts, typically covering 7.5 km per commute. Globally, France took first place for the total distance covered by its participants, followed closely by Finland, Germany, Spain, and China. Suunto’s Commuting Day is a testament to what’s possible when people come together for a common goal. These statistics show that, collectively, we’re reducing emissions, embracing healthier lifestyles, and setting a precedent for sustainable commuting worldwide. Thank you everyone for participating in the Suunto Commuting Day and also the photo contest. Winners of the Suunto Wing open-ear headphones have been contacted directly. Please remember that our small everyday choices make a difference over a longer period of time and together with the community. Keep up the good work! Learn more about tracking human-powered commutes and your CO2e savings Learn more about Suunto sustainability work

A Technological Breakthrough from Tampere University MoniCardi, a medical technology and software company originating from Tampere University, has been diligently developing novel and heart rate variability (HRV) methods to decode the intricate phenomena of the human body. The MoniCardi team aims to unveil the various physiological characteristics influenced by the heart's behavior, opening new frontiers in health and performance measurement. The Foundation: Validation with Massive Datasets MoniCardi's groundbreaking research is rooted in statistical and time-series analysis methods originally developed in computational physics. These methods have surprising, yet highly impactful applications in electrocardiography, including HRV analysis. MoniCardi's novel methods and their usefulness have been validated in various scientific studies [1-9] and they have been featured in the leading conferences of cardiology such as the Scientific Sessions of American Heart Association. The studies include exploitation of massive datasets such as the extensive Finnish Cardiovascular Study (FINCAVAS), which contains comprehensive measurement data from 4386 participants of a clinical stress test. In a recent breakthrough study [1], it was found that MoniCardi's HRV analysis of a one-minute rest phase prior to the test predicts sudden cardiac death significantly better than the conventional analysis of the complete 20-minute stress test (hazard ratios of ~2.5 and ~1.5, respectively). The superiority of MoniCardi increases further when considering all the other risk factors in the analysis. Outside clinical studies, MoniCardi's patented methodology allows accurate estimation of metabolic thresholds in sport applications. This was confirmed in a ground-breaking study published by the team in the leading physiological journal in 2023 [2]. The study was featured in several national and international news sites, including a full-page article in the main Finnish newspaper Helsingin Sanomat (link below). The results are currently under validation in academic collaboration between Tampere University and the Finnish Institute of High-Performance Sport (KIHU). Through a partnership with Suunto launched in 2024, MoniCardi's novel technology is now entering in the use of professional athletes, sport enthusiasts and all the consumers interested in these novel features that push the HRV analysis into a completely new level and ensure practical and actionable results. Understanding Heart Rate Variability (HRV) Heart rate variability (HRV) measures the variation in the time intervals between consecutive heartbeats. By analyzing the fluctuations in these intervals, it is possible to gain insights into the body's state, particularly the autonomic nervous system's influence on the heart. Conventionally, HRV has been used to gauge recovery states during sleep through RMSSD (Root Mean Square of Successive Differences), which observes nightly changes in HRV to detect stress levels. At rest, the body shows significant variability between heartbeats, known as HRV. However, as the body encounters increased stress, the autonomic nervous system shifts into the fight-or-flight mode, resulting in minimal heart rate variability. This reduction in HRV can be used as an indicator to assess stress levels. Introducing DDFA: A Revolutionary Measurement Technology HRV methods are conventionally split into time-domain, frequency-domain and nonlinear methods. One of the most common nonlinear methods is Detrended Fluctuation Analysis (DFA) developed in the early 1990s. The key information provided by DFA is the overall long-term characteristics of HRV in terms of correlations, in particular, how changes in heartbeat intervals at some time affect the changes at another time. This information has powerful predictive value, but the practical usefulness of this information was unleashed only recently, when Dynamical DFA (DDFA) was developed [8,9] and further refined to assess changes in HRV correlations in a time-sensitive manner [10]. In brief, DDFA utilizes a multitude of "measure sticks" from 4 up to >50 consecutive heartbeats. At every instant of time, DDFA then gives a so-called scaling exponent - a characteristic feature of correlations in heartbeat intervals - for all these measure sticks simultaneously. This information can be precisely mapped to the physiological state during physical exercise. Real-Time Intensity Monitoring DDFA excels in assessing real-time changes in the heartbeat correlations during exercise. Training intensity directly correlates with time- and scale-dependent variations in the DDFA scaling exponent. Research indicates that increasing intensity in physical exercise decreases the scaling exponents. Eventually, at very high intensities, the beat-to-beat intervals may show so-called anticorrelations, where large and small beat-to-beat intervals alternate in a specific manner depending on the time scale. This information allows for precise monitoring of exercise intensity and physiological thresholds. Visualizing DDFA in Action A pivotal study, "Estimation of Physiological Exercise Thresholds Based on Dynamical Correlation Properties of Heart Rate Variability," published in Frontiers in Physiology in 2023 [2] illustrates DDFA's capabilities. The research paper presents an exercise scenario where intensity increases over time. The cyan lines denote the two metabolic thresholds: LT1 (aerobic threshold) and LT2 (anaerobic threshold), with the black dotted set on locations where these thresholds would be based blood lactate levels. This illustrates an ideal scenario where the DDFA-based analysis yields threshold levels nearly identical to those obtained using lactate-based threshold definitions. While this represents the optimal case, variations are expected in real applications. The DDFA analysis and lactate-based thresholds may differ from case to case, with heart rate measurements typically matching within +-5 beats per minute. There are also uncertainties inherent in lactate thresholds, which are subject to interpretation. Validity up to clinical accuracy MoniCardi methodology has been used to predict the overall cardiac risk and sudden cardiac death [1], and several cardiac diseases such as long QT syndrome [4,5], atrial fibrillation and congestive heart failure [in preparation]. The methods have also been applied to estimate stress and sleep stages [6,7]. The prediction of sudden cardiac death [1] has gained traction and it was featured in all the big news sites in Finland (YLE, Helsingin Sanomat, Ilta-Sanomat, Aamulehti) and on several international news sites (list below). In medical technology, MoniCardi is currently collaborating with Cardiolex Medical, a Swedish MedTech company developing modern ECG devices and systems. MoniCardi is also seeking partners in wearable technologies to bring cardiac risk assessment to mass markets. References: [1] Jussi Hernesniemi, Teemu Pukkila, Matti Molkkari, Kjell Nikus, Leo-Pekka Lyytikäinen, Terho Lehtimäki, Jari Viik, Mika Kähönen, Esa Räsänen, Prediction of sudden cardiac death with ultra-short-term heart rate fluctuations, JACC: Clinical Electrophysiology, 2024 [2] Matias Kanniainen, Teemu Pukkila, Joonas Kuisma, Matti Molkkari, Kimmo Lajunen, and Esa Räsänen, Estimation of Physiological Exercise Thresholds Based on Dynamical Correlation Properties of Heart Rate Variability, Front. Physiol. 14 (2023). [3] Teemu Pukkila, Matti Molkkari, Matias Kanniainen, Jussi Hernesniemi, Kjell Nikus, Leo- Pekka Lyytikäinen, Terho Lehtimäki, Jari Viik, Mika Kähönen, and Esa Räsänen, Effects of Beta Blocker Therapy on RR Interval Correlations During Exercise, Computing in Cardiology 50 (2023) 10.22489/CinC.2023.104 [4] Matias Kanniainen, Teemu Pukkila, Matti Molkkari, and Esa Räsänen, Effect of Diurnal Rhythm on RR Interval Correlations of Long QT Syndrome, Computing in Cardiology 50 (2023) 10.22489/CinC.2023.287           [5] T. Pukkila, M. Molkkari, J. Kim, and E. Räsänen, Reduced RR Interval Correlations of Long QT Syndrome Patients, Computing in Cardiology 49 (2022) 10.22489/CinC.2022.284 [6] Teemu Pukkila, Matti Molkkari and Esa Räsänen, Dynamical Heartbeat Correlations During Complex Tasks – A Case Study in Automobile Driving, Computing in Cardiology 48 (2021) 10.23919/CinC53138.2021.9662676 [7] M. Molkkari, M. Tenhunen, A. Tarniceriu, A. Vehkaoja, S.-L. Himanen, and E. Räsänen, Non-Linear Heart Rate Variability Measures in Sleep Stage Analysis with Photoplethysmography, Computing in Cardiology 46 (2019); 10.22489/cinc.2019.287 [8] M. Molkkari, G. Angelotti, T. Emig, and E. Räsänen, Dynamical Heartbeat Correlations During Running, Sci. Rep. 10, 13627 (2020) [9] M. Molkkari and E. Räsänen, Robust Estimation of the Scaling Exponent in Detrended Fluctuation Analysis of Beat Rate Variability, Computing in Cardiology 45 (2018); 10.22489/CinC.2018.219 [10] M. Molkkari and E. Räsänen, Inter-beat interval of heart for estimating condition of subject, Patent pending.   Latest news of MoniCardi International news:Science Daily: https://www.sciencedaily.com/releases/2024/06/240613140808.htmScience Alert: https://www.sciencealert.com/new-algorithm-can-predict-and-help- prevent-sudden-cardiac-deathMirage News: https://www.miragenews.com/tampere-university-researchers- predict-sudden-1255528/Medical XPress News: https://medicalxpress.com/news/2024-01-method-based-series-analysis-thresholds.html Finnish news: YLE: https://yle.fi/a/74-20093771Helsingin Sanomat: https://www.hs.fi/tiede/art-2000009847625.htmlIlta-Sanomat: https://www.is.fi/terveys/art-2000010505400.htmlAamulehti: https://www.aamulehti.fi/tiedejateknologia/art-2000010497986.html https://www.aamulehti.fi/tiedejateknologia/art-2000009863997.htmlSTT: https://www.sttinfo.fi/tiedote/70082024/aikasarja-analyysiin-perustuva-uusi-menetelma-helpottaa-urheilun-kynnysarvojen- maarittamista?publisherId=69818730&lang=fi

Have you ever felt that your results are not improving despite consistent training, or that fatigue is not going away? The reason may be the quality of your recovery. In recent years, HRV (heart rate variability) has gained attention from elite athletes to everyday fitness enthusiasts. This article explains what HRV is, how to interpret normal values, what may be happening in the body when HRV is low, and how to use HRV in daily life with a SUUNTO watch. What is HRV? Understanding the basics of heart rate variability HRV (Heart Rate Variability) is a numerical measure of the variation in time between consecutive heartbeats, known as RR intervals. It is easy to assume that if your heart rate is 60 bpm, your heart beats exactly once every second. In reality, there are small differences in timing from one beat to the next. The size of these variations is HRV. The difference between HRV and heart rate Metric What it means Heart rate (HR) The number of heartbeats per minute, for example 60 bpm HRV (heart rate variability) The amount of variation between one heartbeat and the next HRV is important because it is about more than the heart alone. HRV works as an indicator that reflects the balance of the autonomic nervous system. When the parasympathetic nervous system, responsible for relaxation and recovery, is dominant → HRV tends to be higher When the sympathetic nervous system, associated with tension and stress, is dominant → HRV tends to be lower By monitoring HRV over time, you can gain a more objective view of your recovery status and stress level. How to check HRV with SUUNTO | Connecting your watch and app SUUNTO watches automatically measure HRV during sleep. During sleep, the body is at rest, allowing the watch to collect reliable data that is less affected by daytime activity. The measurement uses a metric called RMSSD (Root Mean Square of Successive Differences), which calculates the root mean square of differences between consecutive heartbeat intervals. This is a scientifically established method for quantifying HRV. How to check your HRV data Wear your SUUNTO watch while sleeping and turn on sleep tracking Sync with the Suunto app after waking up, either manually or automatically via Bluetooth Check your HRV data in the app’s Training Zone or mini widget Continue tracking daily so your personal baseline can develop over time SUUNTO calculates your personal “normal range” based on 60 days of data. At least 14 measurements are needed to define the normal range, and at least 3 measurements are needed for the 7-day average. Data appears soon after you start using the feature, but accuracy improves the longer you continue tracking. What is HRV status? Understand recovery at a glance with color In the SUUNTO app, HRV condition is displayed visually as HRV status. Your current 7-day average HRV is compared with your personal normal range and shown as a bar indicator, with colors that make it easy to understand your recovery status at a glance. Display color General status Green Good recovery, ready for training Yellow Recovering, moderate training load recommended Red Insufficient recovery, rest or reduced load needed If HRV rises far above a certain standard deviation, it may also be displayed in yellow or red. This can indicate that the body is mounting a strong recovery response, through parasympathetic activity, to accumulated stress. Interpreting your HRV baseline and normal range HRV varies greatly from person to person, and there is no absolute value that is “normal” for everyone. Because HRV differs depending on age, fitness, physiology, and other factors, it is more important to track your own changes than to compare yourself with others. General tendencies include: Younger people and fit athletes → HRV tends to be higher Older age or high-stress environments → HRV tends to be lower SUUNTO uses an approach based on comparison with your personal normal range, calculated from 60 days of data. This helps you understand whether your current status is above, within, or below your own baseline. What happens when HRV is low? If HRV stays below your normal range, it may be a sign that your body has not recovered sufficiently. Possible effects include: Lower performance, with the same pace feeling more tiring Reduced immune resilience, making you more prone to catching a cold Lower concentration and decision-making ability Loss of motivation A temporary drop in HRV after an intense race or high-intensity training session is a normal response. The concern is when HRV does not recover for several days or more. Main reasons HRV may decrease Training load is not the only reason HRV may drop. Many everyday factors can affect it: Overtraining: Continuing high-intensity training without enough rest Lack of sleep: Both sleep duration and sleep quality are closely linked to autonomic recovery Mental stress: Pressure from work or relationships Poor physical condition: HRV may decrease in the early stages of infections such as colds or influenza Alcohol and irregular eating habits: Alcohol is especially likely to affect nighttime HRV Is higher HRV always better? The idea that “higher HRV is always better” is partly true, but it also needs context. If HRV rises far above the upper end of your normal range, it may indicate that your body is using significant recovery resources in response to strong stress. This does not always mean you are in good condition. What matters most is that HRV is stable within your personal normal range. How to use HRV in daily training By adding HRV data to your training plan, you can train more intelligently and more effectively. Seven practical steps for using HRV: Wear your watch every night and turn on sleep tracking: Continuous measurement helps build your baseline Make morning syncing a habit: Sync with the app and check your HRV status before planning the day. When combined with the SUUNTO Coach AI training plan, training sessions can be suggested automatically based on your HRV status. Compare HRV with training load: Learn how your HRV changes after high-intensity workouts Use it together with resting heart rate: Higher HRV plus lower resting heart rate is a sign of good recovery Reduce training intensity when HRV is low: When the numbers are low, switch to an easy session or a rest day Schedule regular recovery days: Look at HRV trends and intentionally rest 1 to 2 days per week Track sleep, nutrition, and stress as well: HRV is most useful when viewed as part of your overall lifestyle Tip: HRV works as a barometer for your condition. Rather than reacting to each individual number, focus on weekly and monthly trends. SUUNTO watch models that support HRV The following SUUNTO models currently support HRV measurement, meaning HRV tracking during sleep: Model Features Suunto Vertical 2 Latest flagship model. A long-distance adventure watch with up to 65 hours of GPS and an LED light Suunto Vertical Up to 60 days of battery life. A long-distance model with offline maps Suunto Race 2 Latest flagship model. A race-focused watch with high-accuracy sensors and a 1.5-inch AMOLED display Suunto Race S Compact and advanced. Training plans can be automatically optimized through integration with AI Coach Suunto Race Previous-generation Race 2 model. Fully supports HRV measurement and coaching features Suunto Run Lightweight runner-focused model at 36 g. Supports HRV measurement and sleep tracking Suunto Ocean A multisport watch built for both diving and sports, designed to perform underwater as well Suunto 9 Peak Pro Built tough. A durability-focused model popular with outdoor users All models connect with the Suunto app to automatically record and analyze HRV data. Based on accumulated data, they provide personalized feedback on your recovery status. Optimize your recovery with data SUUNTO watches automatically handle everything from nightly HRV measurement to calculating your personal normal range and comparing it with training load. Move from “I feel tired” to understanding recovery through data, and improve the quality of your training with a more scientific approach. ▶ Check SUUNTO watches that support HRV Summary HRV is a metric that quantifies the variation between consecutive heartbeats. It is an important biomarker for objectively understanding the state of the autonomic nervous system and the body’s recovery status. To recap the key points: HRV is the variation between heartbeats. A higher value generally indicates stronger parasympathetic, or recovery-related, activity Normal values vary greatly by individual, so comparison with your own baseline is important Persistently low HRV can be a sign of overtraining, lack of sleep, stress, or other strain Unusually high HRV may also be a body alert that needs attention SUUNTO watches measure HRV automatically during sleep and show it as HRV status in the app Tracking HRV as a daily habit helps you build smarter training plans Using HRV is not only about improving performance. It is also an important habit for improving performance while maintaining long-term health. With a SUUNTO watch, you can read your body’s rhythm through data. Start by understanding your body HRV measurement is useful for everyday health management, even if you are not following a dedicated training plan. With a SUUNTO watch that measures automatically while you sleep, you can start making recovery visible from today. ▶ See the full SUUNTO watch lineup Heart rate variability (HRV) measurement is available on Suunto Vertical 2, Suunto Vertical, Suunto Race 2, Suunto Race, Suunto Race S, Suunto Run, Suunto Ocean, and Suunto 9 Peak Pro GPS watches.