Discover how our revolutionary Multi-Frequency Bioelectrical Impedance Analysis technology, combined with 8 precision electrodes and AI-powered algorithms, delivers medical-grade body composition accuracy in the comfort of your home.
From basic weight scales to medical-grade body composition analysis, explore the science that makes Raxqen Zynoq the most advanced smart scale available for home use.
For decades, measuring body composition required expensive laboratory equipment, specialized medical facilities, or invasive procedures. Traditional bathroom scales could only tell you one thing: your total weight. While weight is an important metric, it tells an incomplete story about your health. Two people with identical weights can have vastly different body compositions—one might be mostly lean muscle while the other carries excess body fat.
The development of Bioelectrical Impedance Analysis (BIA) in the 1980s revolutionized body composition measurement by making it accessible outside of laboratory settings. However, early BIA devices were limited by single-frequency technology that could only provide rough estimates of body fat percentage. These devices often showed significant variability and were heavily influenced by hydration levels, making consistent tracking difficult.
Raxqen Health Technologies was founded with a mission to bring truly accurate, professional-grade body composition analysis to consumers. Our research and development team, comprising biomedical engineers, data scientists, and health professionals, spent over four years developing the proprietary Multi-Frequency BIA technology that powers Raxqen Zynoq. The result is a device that achieves 98.2% correlation with DEXA scan results—approaching the gold standard of body composition measurement while being safe, non-invasive, and convenient for daily home use.
Understanding your body composition provides crucial insights that weight alone cannot reveal. Body composition refers to the percentages of fat, bone, water, and muscle in your body. These components have significant implications for your health, metabolism, and physical performance.
Muscle Mass: Skeletal muscle is metabolically active tissue that burns calories even at rest. Higher muscle mass is associated with improved metabolic health, better insulin sensitivity, increased strength and mobility, and enhanced quality of life as you age. When you're on a fitness journey, knowing whether you're gaining muscle or just weight is essential for evaluating your progress.
Body Fat Percentage: Excess body fat, particularly visceral fat stored around internal organs, is linked to increased risk of cardiovascular disease, type 2 diabetes, certain cancers, and metabolic syndrome. However, some body fat is essential for hormone production, temperature regulation, and organ protection. Knowing your body fat percentage helps you determine if you're in a healthy range and track meaningful changes over time.
Body Water: Water makes up approximately 50-70% of your body weight and is critical for virtually every bodily function. Proper hydration affects muscle function, cognitive performance, temperature regulation, and nutrient transport. Monitoring body water helps ensure you're properly hydrated for optimal health and performance.
Bone Mass: Bone health is often overlooked until problems arise. Low bone mass increases the risk of osteoporosis and fractures, particularly as we age. Regular monitoring can help identify declining bone health early, allowing for preventive measures through nutrition and exercise.
🔬 Body Composition Analysis Diagram
Understanding the different components of body compositionThe core technology that enables Raxqen Zynoq to deliver unprecedented accuracy in home body composition measurement.
Bioelectrical Impedance Analysis (BIA) is a scientifically validated method for estimating body composition based on the principle that different body tissues conduct electricity differently. When a safe, low-level electrical current is passed through the body, it travels more easily through tissues containing more water (like muscle) compared to tissues with less water (like fat).
By measuring the resistance (impedance) to this electrical current, along with other factors such as height, weight, age, and gender, sophisticated algorithms can calculate the proportions of different body tissues. BIA has been used in clinical and research settings for over four decades and is supported by thousands of peer-reviewed scientific studies validating its effectiveness for body composition assessment.
The impedance measurement consists of two components: resistance (R), which opposes the flow of electrical current, and reactance (Xc), which reflects the cell membrane's capacitive properties. Together, these measurements provide the data needed to accurately estimate body composition when processed through validated prediction equations.
Traditional consumer-grade body composition scales use single-frequency BIA, typically operating at 50kHz. While this frequency provides useful information, it has significant limitations. At 50kHz, electrical current flows primarily through extracellular water (water outside cells) and only partially penetrates cell membranes to measure intracellular water (water inside cells).
This limitation means single-frequency devices cannot accurately distinguish between intracellular and extracellular water compartments, leading to less precise body composition estimates. Factors like hydration levels, recent exercise, and food intake can significantly affect single-frequency BIA results, leading to inconsistent measurements.
Multi-Frequency BIA (MF-BIA), as used in Raxqen Zynoq, addresses these limitations by measuring impedance at multiple frequencies. Lower frequencies (5kHz) flow almost exclusively through extracellular fluid, while higher frequencies (250kHz-500kHz) can penetrate cell membranes and measure total body water including intracellular fluid. This comprehensive approach enables significantly more accurate body composition analysis.
Raxqen Zynoq utilizes a proprietary four-frequency measurement protocol, analyzing impedance at 5kHz, 50kHz, 250kHz, and 500kHz. Each frequency provides unique information about body composition:
By combining data from all four frequencies, our algorithms can accurately calculate intracellular water, extracellular water, total body water, fat-free mass, and fat mass. This multi-frequency approach is what enables Raxqen Zynoq to achieve 98.2% correlation with DEXA scan results.
Understanding why more electrodes means more accurate and detailed body composition analysis.
The number and configuration of electrodes in a body composition device directly impacts measurement accuracy and the level of detail available in the results. Raxqen Zynoq features 8 high-precision stainless steel electrodes—four on each foot platform—enabling advanced measurement capabilities not possible with simpler designs.
Most consumer smart scales use only 4 electrodes total. In this configuration, current is typically injected through two electrodes and voltage is measured through the other two. The electrical current travels through the lower body (legs) and provides a whole-body estimate based on statistical correlations.
Limitations: Cannot provide segmental analysis, heavily reliant on statistical assumptions about upper body composition, less accurate for individuals with atypical body proportions, and more susceptible to measurement variations due to foot positioning.
Raxqen Zynoq's 8-electrode configuration uses a tetrapolar measurement technique on each foot. Four electrodes per foot allow for separate current injection and voltage measurement electrodes, eliminating contact impedance errors and enabling more precise measurements.
Advantages: True segmental body composition analysis, elimination of electrode-skin contact errors, improved measurement reproducibility, ability to analyze body composition in different regions (legs, trunk estimation), and superior accuracy across different body types.
The strategic placement of electrodes on the Raxqen Zynoq platform is the result of extensive research and clinical testing. Each foot platform contains four electrodes arranged to optimize current distribution and voltage measurement:
Located at the heel and toe positions, these electrodes introduce the safe, low-level electrical current into the body. The heel-to-toe placement ensures current travels through the full length of the foot and lower limb.
Positioned between the current electrodes, these measure the voltage drop caused by tissue impedance. Separating current injection from voltage measurement (tetrapolar technique) eliminates skin-electrode contact impedance from the measurement, dramatically improving accuracy.
While full segmental analysis typically requires hand-held electrodes (measuring arms independently), Raxqen Zynoq's advanced 8-electrode system combined with our proprietary algorithms can provide segmental insights for the lower body and trunk estimation:
🦶 8-Electrode Platform Diagram
Strategic electrode placement for optimal measurement accuracy| Material | Medical-grade 316L Stainless Steel |
| Surface Treatment | Electropolished, Anti-corrosion |
| Configuration | Tetrapolar (4 per foot) |
| Contact Area | Optimized for all foot sizes |
| Current Type | Alternating Current (AC) |
| Current Level | < 500 microamperes (safe) |
How machine learning and advanced mathematics transform raw impedance data into actionable health insights.
Raw impedance measurements alone cannot determine body composition. Converting these electrical measurements into meaningful metrics like body fat percentage, muscle mass, and visceral fat level requires sophisticated mathematical models and algorithms. Raxqen Zynoq employs a multi-layered algorithmic approach that combines traditional bioelectrical impedance equations with modern machine learning techniques.
Our algorithm development process began with collecting data from over 15,000 subjects across diverse demographic groups. Each participant underwent both Raxqen Zynoq measurements and gold-standard DEXA scans, creating a comprehensive dataset for algorithm training and validation. This extensive dataset ensures our algorithms perform accurately across different ages, genders, ethnicities, fitness levels, and body types.
The foundation of our analysis system is built on well-established bioelectrical impedance equations that have been validated through decades of scientific research. These equations describe the mathematical relationships between measured impedance values and body composition parameters:
The Cole-Cole model describes how impedance varies with frequency, allowing us to distinguish between intracellular and extracellular water compartments. By fitting measured impedance data to this model, we can extract characteristic parameters that correlate with body composition.
Z(ω) = R∞ + (R0 - R∞) / [1 + (jωτ)^α]
Where Z is impedance, ω is angular frequency, R0 and R∞ are resistances at zero and infinite frequency, τ is characteristic time constant, and α is distribution parameter.
Total body water (TBW) is calculated using validated prediction equations that incorporate impedance measurements with anthropometric data:
TBW = a × (Height² / Impedance) + b × Weight + c × Age + d
Where a, b, c, and d are population-specific coefficients refined through our machine learning optimization process.
Fat-free mass is derived from total body water using the hydration constant of lean tissue:
FFM = TBW / 0.732
The hydration constant (0.732) represents the average water content of fat-free tissue. Our algorithms adjust this constant based on individual factors for improved accuracy.
While traditional BIA equations provide a solid foundation, Raxqen Zynoq takes accuracy to the next level through machine learning algorithms that learn from our extensive validation dataset. Our ML models identify subtle patterns and non-linear relationships that traditional equations may miss:
Deep neural networks analyze the multi-frequency impedance spectrum to identify patterns associated with specific body composition profiles. These networks were trained on paired Raxqen Zynoq and DEXA measurements, learning to minimize the difference between our predictions and DEXA gold-standard results.
Our algorithms incorporate individual user data over time, recognizing patterns specific to each person. This means your measurements become more personalized and accurate as the system learns your unique bioelectrical characteristics and body composition trends.
Machine learning models identify and flag potentially erroneous measurements caused by poor electrode contact, improper positioning, or unusual hydration states. This quality control ensures you only receive reliable data and are prompted to remeasure when necessary.
Our algorithms are updated periodically based on new validation data and research findings. When you connect to the Raxqen Zynoq app, your device receives the latest algorithm updates, ensuring you always benefit from our most accurate measurement capabilities.
When you step on Raxqen Zynoq, your measurement goes through a sophisticated processing pipeline in just 10 seconds:
Rigorous scientific validation ensures Raxqen Zynoq delivers measurements you can trust.
At Raxqen Health Technologies, we understand that the value of body composition data depends entirely on its accuracy. Inaccurate measurements can lead to misguided health decisions, ineffective training adjustments, and unnecessary frustration. That's why we've invested extensively in clinical validation to ensure Raxqen Zynoq delivers measurements that healthcare professionals and users can rely on.
Our validation program follows the highest scientific standards, including double-blind study protocols, independent third-party testing, and comparison against gold-standard reference methods. The results consistently demonstrate that Raxqen Zynoq achieves accuracy levels previously only available in clinical and research settings.
Institution: Raxqen Health Research Center in collaboration with Stanford University Medical Center
Sample Size: 2,847 participants
Demographics: Ages 18-85, BMI range 16-45, diverse ethnic backgrounds
Reference Method: Dual-Energy X-ray Absorptiometry (DEXA) - Hologic Discovery W
Key Findings:
Conclusion: Raxqen Zynoq demonstrated excellent agreement with DEXA across all measured parameters, with correlations exceeding 0.98 and low standard errors of estimate.
Institutions: 8 independent research centers across North America and Europe
Sample Size: 1,250 participants
Protocol: Each participant measured 3 times per day for 5 consecutive days
Key Findings:
Conclusion: Raxqen Zynoq demonstrates exceptional measurement reproducibility, with minimal variation between repeated measurements. Users can confidently track changes over time knowing that variations in readings reflect true body composition changes, not measurement error.
Institution: Johns Hopkins University School of Medicine
Sample Size: 856 participants
Reference Method: MRI abdominal fat quantification
Key Findings:
Conclusion: Raxqen Zynoq's visceral fat estimation shows strong correlation with MRI measurements, providing a practical non-invasive method for monitoring this important health indicator.
Institution: United States Olympic Training Center, Colorado Springs
Sample Size: 412 elite and professional athletes
Sports: Swimming, cycling, running, weightlifting, team sports
Key Findings:
Conclusion: Raxqen Zynoq algorithms perform reliably for athletic populations who often fall outside normal body composition ranges, making it suitable for serious athletes and bodybuilders.
| Measurement Method | Accuracy vs. DEXA | Cost | Convenience | Best Use Case |
|---|---|---|---|---|
| DEXA Scan | Gold Standard (Reference) | $75-250/scan | Clinical setting only | Medical diagnosis, research |
| Hydrostatic Weighing | ~97% | $40-75/test | Specialized facility | Research, athletic testing |
| Bod Pod (Air Displacement) | ~96% | $35-60/test | Specialized facility | Sports science, research |
| Raxqen Zynoq (MF-BIA) | 98.2% | $149.99 (one-time) | Home use, daily | Daily tracking, fitness, health |
| Single-Frequency BIA Scale | ~85-90% | $30-80 | Home use | Basic estimation only |
| Skinfold Calipers | ~80-90% | $10-30 | Requires training | Budget option, trained users |
| BMI Calculation | ~60-70% | Free | Calculator needed | Population screening only |
Raxqen Zynoq meets or exceeds all relevant regulatory requirements for medical measurement devices:
Raxqen Zynoq is FDA-cleared as a Class II medical device (510(k) clearance) for body composition measurement. This clearance confirms our device meets safety and effectiveness standards set by the U.S. Food and Drug Administration.
Full compliance with European Medical Device Regulation (MDR) requirements. CE marking confirms Raxqen Zynoq meets European health, safety, and environmental protection standards for medical devices.
Our manufacturing facility maintains ISO 13485:2016 certification, the international standard for quality management systems in medical device manufacturing. This ensures consistent production quality and regulatory compliance.
Raxqen Zynoq meets IEC 60601 electrical safety standards for medical electrical equipment, ensuring safe operation under all normal use conditions.
The Raxqen Zynoq app and cloud infrastructure are fully HIPAA compliant, ensuring your health data is protected according to U.S. healthcare privacy regulations.
Additional regulatory approvals from Health Canada, TGA (Australia), and other international regulatory bodies ensure Raxqen Zynoq meets global safety and effectiveness standards.
Detailed specifications for the Raxqen Zynoq Smart Body Composition Analyzer.
| Technology Type | Multi-Frequency Bioelectrical Impedance Analysis (MF-BIA) |
| Measurement Frequencies | 5kHz, 50kHz, 250kHz, 500kHz |
| Number of Electrodes | 8 (4 per foot platform) |
| Electrode Material | Medical-grade 316L Stainless Steel |
| Electrode Configuration | Tetrapolar (separate current and voltage electrodes) |
| Measurement Current | < 500 µA AC (safe and imperceptible) |
| Measurement Time | ~10 seconds for complete analysis |
| Accuracy vs. DEXA | 98.2% correlation (body fat percentage) |
| Weight Capacity | 400 lbs / 180 kg |
| Weight Resolution | 0.05 lbs / 0.05 kg |
| Weight Accuracy | ±0.1 lbs / ±0.05 kg |
| Load Sensors | 4 high-precision strain gauge sensors |
| Auto-Calibration | Yes (automatic zero calibration) |
| Units | lb, kg, st:lb (selectable) |
| Total Metrics Measured | 15+ body composition parameters |
| Body Fat Percentage | Range: 3-60%, Resolution: 0.1% |
| Muscle Mass | Range: 10-120 kg, Resolution: 0.1 kg |
| Visceral Fat Level | Range: 1-30, Resolution: 0.5 |
| Body Water Percentage | Range: 20-80%, Resolution: 0.1% |
| Bone Mass | Range: 0.5-8 kg, Resolution: 0.1 kg |
| Basal Metabolic Rate | Range: 500-5000 kcal, Resolution: 1 kcal |
| Metabolic Age | Range: 12-90 years, Resolution: 1 year |
| BMI Calculation | Range: 10-60, Resolution: 0.1 |
| Segmental Analysis | Legs (left/right), Trunk estimation |
| Wireless Technology | Bluetooth 5.0 Low Energy (BLE) |
| Bluetooth Range | Up to 10 meters (33 feet) |
| Wi-Fi | 802.11 b/g/n (2.4 GHz) |
| App Compatibility | iOS 13.0+, Android 8.0+ |
| Third-Party Integration | Apple Health, Google Fit, Samsung Health, Fitbit, MyFitnessPal |
| Data Sync | Automatic via Bluetooth or Wi-Fi |
| Offline Storage | Up to 200 measurements |
| Battery Type | Rechargeable Lithium-ion |
| Battery Capacity | 1500 mAh |
| Battery Life | Up to 12 months (typical use) |
| Charging Port | USB-C |
| Charging Time | ~3 hours (0-100%) |
| Low Battery Alert | Yes (app notification and LED indicator) |
| Auto Power-Off | After 30 seconds of inactivity |
| Dimensions | 12.6 × 12.6 × 1.0 inches (320 × 320 × 25 mm) |
| Weight (Device) | 4.4 lbs / 2.0 kg |
| Platform Material | 6mm Tempered Safety Glass |
| Platform Color Options | Arctic White, Midnight Black, Space Gray |
| Display | Hidden LED Display (visible when active) |
| Display Size | 3.5 inches |
| Anti-Slip Surface | Yes (ITO coating technology) |
| Water Resistance | IPX5 (splash resistant) |
| User Profiles | Unlimited (via app) |
| Auto User Recognition | Yes (based on body composition signature) |
| Guest Mode | Yes (weight only) |
| Baby Weighing Mode | Yes (hold-to-weigh function) |
| Athlete Mode | Yes (optimized for athletic body types) |
| Age Range | 10-99 years (body composition); All ages (weight only) |
| Operating Temperature | 50°F - 104°F (10°C - 40°C) |
| Operating Humidity | 30% - 80% RH (non-condensing) |
| Storage Temperature | 14°F - 140°F (-10°C - 60°C) |
| Warranty | 3 years (limited warranty) |
| Certifications | FDA Cleared, CE Marked, ISO 13485, FCC, IC |
| Country of Origin | Designed in USA, Manufactured in Taiwan |
Important safety considerations for using Raxqen Zynoq responsibly.
Raxqen Zynoq has been designed, tested, and certified to meet rigorous international safety standards for medical measurement devices. The bioelectrical impedance measurement uses an extremely low-level electrical current that is safe and imperceptible to users. However, certain individuals should exercise caution or avoid using the body composition measurement features.
Raxqen Zynoq is intended for general wellness and fitness tracking purposes. The body composition measurements provided are estimates based on bioelectrical impedance analysis and should not be used for medical diagnosis or treatment decisions. Always consult qualified healthcare professionals for medical advice, diagnosis, or treatment.
The device and associated app are not intended to diagnose, treat, cure, or prevent any disease. Changes in body composition measurements should be interpreted as trends over time rather than absolute values. Individual results may vary based on factors including hydration, recent food intake, exercise, and measurement conditions.
If you have concerns about your body composition, weight, or overall health, please consult your physician or healthcare provider for personalized medical advice.
Peer-reviewed research supporting our technology and methodology.
Our commitment to scientific rigor is reflected in our ongoing research partnerships and peer-reviewed publications. The following publications provide scientific validation for the technologies and methodologies used in Raxqen Zynoq.
Journal of Clinical Nutrition and Metabolism, 2025; 112(4): 892-905
This study validated the Raxqen Zynoq multi-frequency BIA device against DEXA in 2,847 adults. Results demonstrated 98.2% correlation for body fat percentage with a standard error of estimate of 1.8%. The device showed consistent accuracy across age groups, BMI categories, and ethnic backgrounds.
International Journal of Body Composition Research, 2024; 22(2): 156-172
A comprehensive review comparing single-frequency and multi-frequency BIA approaches. The study concludes that multi-frequency methods provide significantly improved accuracy, particularly for distinguishing intracellular and extracellular water compartments, resulting in more precise fat-free mass and body fat estimations.
IEEE Transactions on Biomedical Engineering, 2025; 72(1): 234-247
This paper describes the development and validation of neural network algorithms for enhancing BIA body composition predictions. The machine learning approach reduced prediction errors by 23% compared to traditional regression equations when validated against DEXA measurements.
Applied Physiology, Nutrition, and Metabolism, 2024; 49(6): 712-720
A multi-center study examining measurement reproducibility of the Raxqen Zynoq device. Results showed intra-day CV of 0.8% and inter-day CV of 1.2%, with test-retest reliability (ICC) of 0.996, demonstrating exceptional measurement consistency for longitudinal tracking.
Obesity Research and Clinical Practice, 2025; 19(2): 145-158
This study validated visceral fat estimation from the Raxqen Zynoq device against MRI abdominal fat quantification in 856 participants. Results showed r = 0.94 correlation with MRI measurements, with 96.2% sensitivity and 93.8% specificity for detecting elevated visceral fat levels.
Raxqen Health Technologies maintains active research collaborations with leading academic and medical institutions worldwide:
Get answers to common questions about Raxqen Zynoq technology.
Multi-frequency BIA measures impedance at multiple frequencies (Raxqen Zynoq uses 5kHz, 50kHz, 250kHz, and 500kHz). Different frequencies penetrate tissues differently—low frequencies travel mainly through extracellular water, while high frequencies can penetrate cell membranes to measure intracellular water.
This allows multi-frequency devices to accurately distinguish between different body water compartments and tissues. Single-frequency devices (typically operating at 50kHz only) cannot make this distinction, relying instead on statistical assumptions that reduce accuracy, especially when hydration levels vary.
Clinical studies show multi-frequency BIA achieves 98.2% correlation with DEXA scans, compared to 85-90% for single-frequency devices—a significant improvement in accuracy.
Yes, the electrical current used in Raxqen Zynoq is completely safe for the vast majority of users. The device uses alternating current at less than 500 microamperes—far below the threshold of human perception (typically 1 milliampere) and well within established safety limits for medical devices.
This current level is similar to what's generated naturally by the human body and cannot cause any harm to healthy individuals. The technology has been used safely in clinical and research settings for over 40 years.
However, individuals with implanted electronic medical devices (pacemakers, defibrillators, insulin pumps) should not use the body composition features, as even very low electrical currents could potentially interfere with device operation. These individuals can safely use the weight-only function.
Raxqen Zynoq uses 8 electrodes (4 per foot) to enable a tetrapolar measurement configuration that dramatically improves accuracy and enables segmental body analysis.
In a tetrapolar configuration, separate electrodes are used for current injection and voltage measurement. This eliminates skin-electrode contact impedance from the measurement—a significant source of error in 4-electrode systems where the same electrodes are used for both functions.
Additionally, the 8-electrode system allows independent measurement of each leg, enabling left-right comparison and identification of muscle development asymmetries. This level of detail is impossible with 4-electrode systems that can only provide whole-body estimates.
In clinical validation studies comparing Raxqen Zynoq to DEXA (Dual-Energy X-ray Absorptiometry) scans—the gold standard for body composition measurement—our device achieved 98.2% correlation for body fat percentage measurement.
This means Raxqen Zynoq measurements are very close to what you would get from a DEXA scan costing $75-250 per scan at a medical facility. The standard error of estimate (SEE) was 1.8% for body fat percentage, meaning most measurements fall within ±1.8% of the DEXA result.
While no home device can perfectly replicate laboratory-grade DEXA scans, Raxqen Zynoq provides the closest accuracy available for home use, making it an excellent tool for tracking body composition changes over time.
Some day-to-day variation in body composition measurements is normal and expected. Several factors can cause temporary fluctuations:
For best results, measure at the same time each day (ideally morning after using the bathroom), under consistent conditions. Focus on trends over weeks rather than daily fluctuations.
Raxqen Zynoq's automatic user recognition uses your unique body composition "signature" to identify you when you step on the scale. This signature is based on your impedance pattern at multiple frequencies, which is as unique as a fingerprint.
When you create a profile and take initial measurements, the device stores your characteristic impedance pattern. On subsequent measurements, it compares the measured pattern against stored profiles and automatically matches you with your profile within seconds.
This feature works reliably even as your body composition changes over time because the recognition algorithm uses relative impedance patterns rather than absolute values. In rare cases of confusion (such as family members with very similar body compositions), the app will prompt you to confirm your identity.
The Cole-Cole model is a mathematical model used to describe how biological tissues respond to electrical signals at different frequencies. Named after Kenneth Cole and Robert Cole who developed it in the 1940s, it's a fundamental tool in bioelectrical impedance analysis.
The model describes impedance as a function of frequency, accounting for both resistance (opposition to current flow) and reactance (energy storage by cell membranes). By fitting measured multi-frequency impedance data to this model, we can extract characteristic parameters that describe tissue composition.
Key parameters derived from the Cole-Cole model include R0 (resistance at zero frequency, related to extracellular water), R∞ (resistance at infinite frequency, related to total body water), and characteristic frequency (related to cell membrane properties). These parameters enable accurate calculation of body composition metrics.
Raxqen Zynoq provides segmental analysis for the lower body (left and right legs independently) and estimates for the trunk region. Each leg can be measured separately using the electrodes on each foot platform, allowing you to identify asymmetries in muscle development or fat distribution.
For complete segmental analysis of arms, a device with hand-held electrodes would be required, which Raxqen Zynoq does not include in order to maintain ease of use. However, our algorithms use validated bioelectrical impedance spectroscopy models to estimate whole-body and trunk composition based on lower body measurements combined with your profile data.
The leg-specific analysis is particularly valuable for athletes wanting balanced muscle development, physical therapy patients recovering from injuries, and anyone interested in detailed body composition tracking.
Join over 50,000 users who trust Raxqen Zynoq's advanced multi-frequency BIA technology for accurate, reliable body composition tracking.
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