Science-based self care, driven by AI

Project AIvive- An AI-Powered Personalized Prevention System

At AIvive, we are on a mission to transform reactive sick-care into proactive and predictive wellcare. Recent advances in artificial intelligence are enabling a paradigm shift in precision medicine by extracting deep personalized insights from multifaceted health data.

  1. Continuous Monitoring with Wearable Devices: Miniaturized wearable devices  can be adhered to the skin to continuously track body sounds. These devices are particularly useful in continuously monitoring sounds related to cardiorespiratory function, gastrointestinal activity, swallowing, and respiration. In pilot studies involving premature babies and adults, including those with chronic lung diseases, these devices have shown clinical-grade accuracy and offered functionalities not previously available in research or clinical care​​.

  2. Advanced Wearable Sensors for Telehealth: There has been a rapid expansion in the development and use of wearable sensors, with a compound annual growth rate of 18.3% from 2021 to 2030. These sensors are critical in telehealth, monitoring biological, mechanical, temperature, and other signals. Developments in sensing materials and flexible electronics have considerably advanced this field, enabling real-time and remote health monitoring. These sensors can monitor a wide range of physiological parameters and body movements, providing continuous data for health condition monitoring​​.

  3. Transformation of Healthcare with Wearables: Wearable devices, along with advanced sensors and AI technologies, are expected to transform healthcare significantly. These wearables are set to improve continuous biomarker monitoring, such as noninvasive blood glucose and blood pressure measurements. They will enable monitoring of multiple biomarkers for a holistic view of health, transition healthcare from reactive to proactive, and facilitate monitoring outside of hospital settings. AI will play a larger role in interpreting health data collected by wearables, leading to more intelligent healthcare. By 2024, it is anticipated that the number of health and wellness wearables shipped worldwide will rise to nearly 440 million​​​​​​​​​​.

These advancements in wearable technology and sensor development are crucial for health monitoring, aligning with the goals of your AIHealthGuard project. They indicate a shift towards more personalized, continuous, and non-invasive health monitoring, leveraging the latest in sensor technology and AI.

Our vision is an integrated health loop where patients are continuously monitored by a personalized AI agent that provides science-based guidance to optimize wellbeing while alerting providers when clinical care is appropriate.

We foresee a future where many diseases can be prevented altogether and people universally maintain optimized health – not just treat illnesses when they arise. At AIvive, our mission is to bring precision wellcare into reality through the power of artificial intelligence.



Recent research demonstrates the immense potential of flexible and stretchable electronics for continuous health monitoring. Conformal biosensors constructed from soft, active materials have achieved clinical-grade measurements of temperature, heart rate, respiration rate, blood oxygen, electrocardiography signals, and more while woven into everyday clothing. Tiny flexible modules mounted directly on the skin can also track biomarkers in sweat such as glucose levels. Powered wirelessly, such systems generate big datasets ripe for analysis by AI for diagnostics, early disease detection, evaluation of therapies, and overall personalized health management.

Importantly, flexible form factors improve user comfort and accessibility over rigid electronics. As AIvive aims to integrate multi-parameter monitoring into lifestyle products, stretchable electronic technologies possessing soft mechanical properties closely matching human tissues will be key enablers in achieving this vision. Ongoing stretchable systems research focused on driving higher channel counts, better signal resolution, and greater on-board computation power promises continued advances.

Recent advances in smart textiles and wearable technology enable clothing to continuously monitor a wide range of vital signs and biometrics. Conductive threads and flexible printed circuits allow sensors to be seamlessly integrated into the fabric without affecting comfort or aesthetics.

Shirts have been developed that can measure ECG, respiration rate, temperature, activity, and more. Legwear can track EMG signals and joint movements. Headwear is being designed to monitor EEG. Smart garments can now unobtrusively measure over 20 distinct physiological parameters.

This data can be analyzed by AI algorithms to provide diagnostics, predict emerging health issues, evaluate therapies, and offer personalized health insights. The large datasets generated by continuous multi-parameter monitoring from thousands of users offers immense potential to train advanced neural networks.

For the AIvive project, smart garments is a key enabling technology. By partnering with companies developing sensor-embedded clothing, AIvive can gain access to rich biomechanical data from users performing everyday activities. This real-world data can allow AIvive to develop precise and personalized health tracking solutions.

As comfort and functionality of smart garments improves, user adoption will increase. This will provide AIvive with exponential growth in training data volume and variety – fueling breakthroughs in predictive health algorithms.

 Wearable sensors can detect a wide range of health indicators. These include body motions, vital signs (like breath, heart rate, ECG, blood pressure, skin temperature, SpO2), and metabolism parameters (such as glucose, pH, electrolytes, lactic acid). 

Smart garments is a key enabling technology. By partnering with companies developing sensor-embedded clothing, AIvive can gain access to rich biomechanical data from users performing everyday activities. This real-world data can allow AIvive to develop precise and personalized health tracking solutions.

As comfort and functionality of smart garments improves, user adoption will increase. This will provide AIvive with exponential growth in training data volume and variety – fueling breakthroughs in predictive health algorithms.

The importance of continuously monitoring vital signs, especially in high-risk groups, is highlighted. Many of these vital signs are critical indicators of serious diseases like heart attacks, hypertension, and asphyxia. Wearable sensing electronics have revolutionized the detection of these vital signs​​.

  1. Blood Pressure (BP) Monitoring: Traditional BP measurement methods are obtrusive and discrete, potentially missing vital signs that occur sporadically. This has led to the development of wearable, cuffless BP monitoring systems that integrate sensors into devices like wristbands or earphones. These sensors collect physiological signals for BP calculation using physiological or machine learning models​​.

  2. Tonoarteriogram (TAG) Sensors: TAG sensors are used for continuous arterial BP monitoring. Their flexibility allows for excellent conformity to human skin, enabling them to capture tiny pressure variations caused by pulse waves. This cuffless method offers continuous pulse monitoring with minimal discomfort to the user​​.

  3. ECG and Bioimpedance Electrodes: Electrocardiogram (ECG) signals, recorded by electrodes attached to the skin, are crucial for monitoring heart activity. ECG electrodes come in wet, dry, and capacitively coupled types, each with its specific advantages and uses. These electrodes are also used for bioimpedance monitoring, which can provide additional features for BP calculation algorithms​​.

  4. Optical Sensors: Photoplethysmogram (PPG) devices, consisting of light sources and photodetectors, are used to monitor cardiac-induced changes in microvascular blood volume. PPG sensors are typically placed at peripheral body sites and have been integrated into various wearable devices, including eyeglasses and pulse oximeters​​.

  5. Ultrasound Sensors: These sensors are noninvasive and suitable for BP waveform monitoring. Flexible wearable ultrasound sensors have been developed, overcoming the limitations of traditional ultrasound probes. They allow for long-term, continuous monitoring of BP and heart rate​​.

  6. Noise Reduction Techniques: Reducing noise in biosignals is crucial for accurate vital signs monitoring. Various techniques are employed to minimize interference from external factors like power-line interference, electromagnetic noise, and motion artifacts​​.

  7. Machine Learning in BP Monitoring: Machine learning, including both traditional algorithms and deep learning, is increasingly being used for algorithmic beat-to-beat BP estimation. These methods can offer end-to-end predictions and are critical in enhancing the accuracy and reliability of BP monitoring systems​​.

These advancements in wearable sensors and their associated technologies represent a significant leap forward in vital signs monitoring, moving towards more accurate, less invasive, and user-friendly methods. This aligns well with AIvive’s mission of transforming healthcare into a more proactive and predictive model, utilizing the latest in sensor technology and AI.


The monitoring of metabolism parameters is a critical aspect of health monitoring, and it’s particularly relevant for AIvive’s focus on proactive and predictive healthcare. 

  1. Importance of Metabolism Parameters: Metabolism parameters include various ionized metals, metabolites, and the body’s acid-base balance. These parameters are essential for the proper functioning of organs, and excessive variations in these parameters can lead to detrimental health effects. Thus, monitoring these parameters is crucial for maintaining overall health and early detection of potential health issues.

  2. Conventional vs. Wearable Monitoring Methods: Traditionally, monitoring metabolism parameters involves collecting and testing blood samples. This process can be invasive, tedious, and time-consuming. In contrast, wearable sensors offer a non-invasive and continuous approach to monitoring these parameters. Such advancements are particularly beneficial in reducing discomfort and providing real-time data for proactive health management.

  3. Use of Bio-Chemical Sensors: To monitor metabolism parameters non-invasively, many conformal bio-chemical sensors have been developed. These sensors are capable of measuring electrolytes and metabolites in excrements from the body surface, providing valuable data about the body’s metabolic state.

  4. Sweat Analysis: Sweat is a commonly used bio-fluid in non-invasive monitoring approaches. The electrolyte and metabolite levels in sweat are closely related to those in blood plasma, making it a valuable source for monitoring metabolic health. For example, levels of calcium (Ca2+), sodium (Na+), potassium (K+), chloride (Cl-), and heavy metals in sweat can provide insights into the body’s metabolic processes and potentially detect imbalances or deficiencies.

  5. Integration with AIvive’s Objectives:  incorporating the monitoring of metabolism parameters into the AI-powered system enhance the ability to provide personalized health insights. By continuously tracking these parameters, AIvive can identify trends or anomalies that may indicate a risk of metabolic disorders or other health issues. This information is pivotal in shifting from reactive to proactive healthcare, allowing for timely interventions and personalized health guidance.

In summary, the ability to non-invasively and continuously monitor metabolism parameters using wearable bio-chemical sensors represents a significant advancement in health technology. This capability aligns perfectly with AIvive’s mission of transforming healthcare through AI-powered personalized monitoring and prevention, offering a more comprehensive and real-time picture of an individual’s health status.

A dual-mode fiber-shaped flexible capacitive strain sensor fabricated by direct ink writing technology for wearable and implantable health monitoring applications.

  1. Advanced Sensor Technology: The fiber-shaped flexible capacitive strain sensor (FSFCSS) developed using direct ink writing (DIW) technology demonstrates dual-mode strain sensing – axial tensile strain and radial expansion strain. This sensor offers a wide detection range, high sensitivity, and responsiveness to static and dynamic expansion strain, making it ideal for wearable health monitoring and human-machine interaction.

  2. Versatility and Integration: The FSFCSS can be integrated into clothing and gloves, allowing for real-time collection of human posture information and gesture movements. This opens up a wide range of applications in human-machine interaction, which is valuable for AIvive in developing interactive health monitoring solutions.

  3. Hemodynamic Monitoring: The sensor’s radial expansion strain sensing capabilities enable its application in real-time acquisition of hemodynamic information. This is crucial for postoperative monitoring, especially in patients with coronary artery disease, potentially allowing AIvive to extend its monitoring capabilities to post-surgical care and implantable monitoring systems.

  4. Customization and Performance: The FSFCSS is customizable and fabricated with a high-precision DIW device, offering excellent performance in both sensing modes. Its capacity to capture subtle skin vibrations and joint strain enables real-time and continuous capture of physiological health signals, contributing to advancements in wearable health monitoring – a key focus for AIvive

The sensing mechanisms employed in wearable health monitoring devices are crucial for the accurate and reliable tracking of health indicators.  

  1. Piezoresistivity:

    • Principle: Piezoresistive sensors work on the principle that their electrical resistance changes when mechanical stress is applied. This change in resistance can be measured and translated into data regarding the applied force or strain.
    • Applications: These sensors are widely used for motion detection, given their sensitivity to changes in pressure and strain. They can also be used to measure temperature, pH, analyst concentration, and humidity. This versatility makes piezoresistive sensors particularly useful for wearable health monitoring systems where different types of data need to be gathered from a single, compact device​​.
  2. Capacitance:

    • Principle: Capacitive sensors operate based on the storage of electrical charge between two plates separated by a dielectric material. When there’s a change in the physical, chemical, or biological stimuli (like displacement of the plates or change in the permittivity of the dielectric), the capacitance changes. This change can be measured to provide data about the applied load or stimulus.
    • Applications: These sensors are suitable for detecting various physical parameters, and their ability to detect changes in dielectric properties makes them useful in monitoring different types of biological signals​​.
  3. Piezoelectricity:

    • Principle: Piezoelectric sensors use materials (usually non-centrosymmetric crystals) that generate electric charges when external mechanical stimuli are applied. This electromechanical interaction converts mechanical energy into electrical signals.
    • Applications: Piezoelectric sensors are beneficial in wearable health devices for tracking movements or other mechanical changes. Due to their direct energy conversion mechanism, they are efficient in environments where power conservation is crucial​​.
  4. FET-based Sensors:

    • Principle: FET (Field-Effect Transistor) based sensors incorporate sensitive resistors or capacitors into a traditional transistor setup. This configuration can be seen as an expansion of the piezoresistivity or capacitance mechanisms.
    • Applications: FET sensors are ideal for flexible tactile sensing due to their excellent transduction and amplification functionality, potential for mass production, and low power consumption. They are particularly adept at reducing crosstalk between sensing pixels, making them suitable for high-resolution sensing arrays in wearable devices​​.

Each of these sensing mechanisms contributes uniquely to the field of wearable health monitoring. Piezoresistive and capacitive sensors are versatile in tracking various physical and biological parameters. Piezoelectric sensors offer efficient energy conversion for motion detection. FET-based sensors bring high-resolution and low-power consumption to the table, enhancing the functionality of wearable devices.

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What e various types of signals that can be tracked by different wearable health sensors, including capacitive, piezoresistive, piezoelectric, and optical sensors. Each type of sensor is connected to the specific health signals they are capable of monitoring:

  1. Heart Rate: Monitored by several sensor types, indicated by a heart icon.

  2. Respiration: Tracked by sensors that can detect breathing patterns and rate, shown with lungs icon.

  3. Blood Pressure: Represented by a blood pressure cuff icon, indicating sensors capable of monitoring blood pressure.

  4. Body Temperature: Illustrated by a thermometer icon, showing the ability of sensors to measure temperature.

  5. Blood Oxygen Levels: Indicated with an oxygen mask icon, for sensors that can monitor oxygen saturation in the blood.

  6. Sleep Patterns: Demonstrated with a moon and stars icon, for sensors that track sleep quality and patterns.

  7. Body Movement: Shown with a human figure in motion, representing sensors that detect physical activity and movement.