Approaches of wearable and implantable biosensor towards of developing in precision medicine

Frontiers in Medicine 01 frontiersin.org Approaches of wearable and implantable biosensor towards of developing in precision medicine ElhamGhazizadeh 1,2, ZahraNaseri 2, Hans-PeterDeigner 3,4,5, HosseinRahimi 6 and ZeynepAltintas 1* 1 Department of Bioinspired Materials and Biosensor Technologies, Faculty of Engineering, Institute of Materials Science, Kiel University, Kiel, Germany, 2 Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran, 3 Institute of Precision Medicine, Furtwangen University, Villingen-Schwenningen, Germany, 4 Fraunhofer Institute IZI (Leipzig), Rostock, Germany, 5 Faculty of Science, Eberhard-Karls-University Tuebingen, Tuebingen, Germany, 6 Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States In the relentless pursuit of precision medicine, the intersection of cuttingedge technology and healthcare has given rise to a transformative era. At the forefront of this revolution stands the burgeoning field of wearable and implantable biosensors, promising a paradigm shift in how wemonitor, analyze, and tailor medical interventions. As these miniature marvels seamlessly integrate with the human body, they weave a tapestry of real-time health data, offering unprecedented insights into individual physiological landscapes. This log embarks on a journey into the realm of wearable and implantable biosensors, where the convergence of biology and technology heralds a new dawn in personalized healthcare. Here, we explore the intricate web of innovations, challenges, and the immense potential these bioelectronics sentinels hold in sculpting the future of precision medicine. KEYWORDS wearable, implantable, biosensors, precision medicine, health Introduction Precision medicine represents a paradigm shift in healthcare, aiming to tailor medical interventions to individual characteristics, allowing for more personalized and effective treatments. The role of precision medicine in developing healthcare and treatment is not just about individualized care; it signifies a paradigm shift towards a more proactive, informed, and patient-centric healthcare system (1). As our understanding of genetics deepens and technology continues to evolve, precision medicine will undoubtedly play an increasingly pivotal role in shaping the future of healthcare, offering a level of precision and effectiveness that was once deemed the stuff of futuristic visions. In this new era, healthcare is not just about treating diseases; it’s about understanding and optimizing the unique genetic tapestry of each individual for a healthier, more resilient tomorrow (2). Wearable and implantable biosensors have emerged as key enablers in this transformative journey, offering continuous, real-time monitoring of physiological parameters. On the other front, wearable biosensors have ushered in a new era of healthcare by providing a continuous stream of data about an individual’s physiological status. These devices, ranging from smartwatches and fitness trackers to more specialized medical-grade sensors, can monitor parameters such as heart rate, blood pressure, glucose levels, and even more complex metrics like ECG patterns. Wearable biosensors OPEN ACCESS EDITED BY Ashutosh Kumar, University of Notre Dame, UnitedStates REVIEWED BY Amit Kumar Yadav, Jawaharlal Nehru University, India Damini Verma, Indian Institute of Technology Roorkee, India *CORRESPONDENCE Zeynep Altintas [email protected] RECEIVED 23 February 2024 ACCEPTED 30 April 2024 PUBLISHED 18 July 2024 CITATION Ghazizadeh E, Naseri Z, Deigner H-P, Rahimi H and Altintas Z (2024) Approaches of wearable and implantable biosensor towards of developing in precision medicine. Front. Med. 11:1390634. doi: 10.3389/fmed.2024.1390634 COPYRIGHT © 2024 Ghazizadeh, Naseri, Deigner, Rahimi and Altintas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Review PUBLISHED 18 July 2024 DOI 10.3389/fmed.2024.1390634 Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 02 frontiersin.org offer a real-time, comprehensive view of a person’s health, enabling early detection of anomalies and facilitating proactive healthcare interventions (3). Wearable biosensors, integrated into clothing or accessories, provide a non-intrusive means of collecting a wealth of data, including vital signs, activity levels, and even biochemical markers. These devices empower individuals to actively participate in their healthcare, fostering a proactive approach to well-being. Moreover, the seamless integration of data from wearables into electronic health records facilitates a comprehensive understanding of a patient’s health status (4). Implantable biosensors, on the other hand, delve deeper into the intricacies of the human body, offering unprecedented access to internal physiological processes. These miniaturized marvels are designed to monitor specific biomarkers, providing clinicians with intricate insights into disease progression and treatment response. The potential for early detection of anomalies and swift intervention holds promise for preventing diseases before they manifest clinically (5). The synergy between wearable and implantable biosensors contributes to a holistic approach to precision medicine. Continuous data streams from wearables serve as a foundation for baseline health, while implantable offer focused, in-depth information on specific parameters. Integrating this wealth of data through advanced analytics and artificial intelligence not only refines diagnostics but also enhances predictive modeling for treatment outcomes (6). The amalgamation of real-time, personalized data from these devices holds the promise of transforming healthcare from reactive to proactive, offering a future where medical interventions are precisely tailored to individual needs, optimizing outcomes, and improving the overall quality of life. This review explores the pivotal role of these biosensors in advancing precision medicine. Precision medicine and wearable/ implantable biosensor In the relentless pursuit of improving healthcare outcomes, precision medicine has emerged as a revolutionary paradigm, challenging the conventional one-size-fits-all approach. Unlike traditional medicine, which often employs generalized treatments, precision medicine tailor’s healthcare strategies to the unique genetic, environmental, and lifestyle characteristics of each individual. This bespoke approach not only transforms the landscape of diagnosis and treatment but holds the potential to redefine the entire healthcare experience (7, 8). Armed with genetic insights, healthcare providers can identify potential health risks long before symptoms manifest. This early detection empowers a proactive approach to healthcare, where interventions can beimplemented to prevent the onset of diseases or manage them at their earliest stages (9). This knowledge allows healthcare professionals to prescribe drugs that are not only effective but also tailored to each patient, minimizing the trial-anderror process often associated with medication regimens. Precision medicine contributes to a deeper understanding of diseases at the molecular level. This knowledge not only aids in more accurate diagnoses but also fuels ongoing research, leading to the development of innovative therapies that target the specific mechanisms driving diseases (10). In the ever-evolving landscape of healthcare, the convergence of precision medicine and wearable biosensors has emerged as a groundbreaking frontier, promising personalized and real-time insights into an individual’s health. Precision medicine, which tailors medical care to the unique characteristics of each patient, and wearable biosensors, compact devices that continuously monitor physiological parameters, are joining forces to revolutionize how we approach diagnosis, treatment, and overall healthcare management (11). When precision medicine and wearable biosensors intersect, the synergy created is nothing short of transformative. Imagine a scenario where a patient’s genetic predisposition to a particular condition is combined with real-time data from wearable biosensors, allowing healthcare providers to predict, prevent, or manage diseases with unprecedented accuracy (12, 13). By integrating genetic data with continuous monitoring, healthcare professionals can identify early signs of diseases or health risks, enabling preventive measures to beimplemented before symptoms manifest. Personalized treatment plans, informed by both genetic insights and real-time physiological data, ensure that interventions are tailored to an individual’s unique profile. This targeted approach enhances treatment efficacy and reduces the risk of adverse reactions (14, 15). Wearable biosensors enable remote patient monitoring, allowing healthcare providers to track a patient’s health in real-time without the need for frequent clinic visits (16). This is particularly beneficial for individuals with chronic conditions or those recovering from surgery. The wealth of data generated by wearable biosensors, when analyzed in conjunction with genetic information, contributes to a deeper understanding of the factors influencing health outcomes (17). This data-driven approach facilitates ongoing research, leading to continuous improvements in precision medicine (Figure1). Here, wehave compiled a summary of recent advances in the development of wearable biosensors for monitoring health and disease-related symptoms with the aim of ameliorating various health-threatening diseases in different organs of the body. Wearable/implantable technology and applications in cardiovascular care In 2003, Cardionet Inc. developed the first mobile telemetry system, which recorded ECG and uploaded ambulatory data via cellular connections. It also contained algorithms for automatically transmitting and detecting asymptomatic and symptomatic events (18). Over the past five to 10 years, advanced technologies have emerged, targeting consumers and businesses. The most commonly used accelerometer is found in phones, wrists, and textiles. Accelerometers detect acceleration by measuring sensor displacement or mechanical stress applied in the system. They can also beused for heart sound monitoring by evaluating auditory vibrations, detecting conditions based on intensity, frequency, quality, and duration. However, noise from motion artifacts is a major limitation (19). Ballistocardiogram (BCG) is an accelerometer-based technique that detects cardiac motion, allowing for the detection of heart rate, blood pressure, and myocardial contractility (20). Seismocardiogram (SDG) uses a chest wall sensor to detect chest wall vibrations, gathering information on heart rate, blood pressure, and cardiac output (21, 22). Photoplethymography (PPG) detects variations in Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 03 frontiersin.org blood pressure within microvasculature. It can be used with smartphones or accessory devices to measure pulsatile activity, detecting heart rate and heart rhythm, but measurements can beaffected by body movement, temperature, hair, skin color, and tattoos (23, 24). Electrode-based technology is increasingly used in healthcare monitoring, recording single-lead electrocardiograph (ECG) using two vectors. These techniques can detect heart rate and rhythm, as well as ischemia, but these readings are subject to noise and artifacts and are limited to a single lead analysis. There are already several commercialized wearable ECG devices in the market including smartwatches, such as those offered by companies like Apple, Fitbit, and Samsung, often include ECG functionality as a feature (Figures2A,B). These devices can measure heart rate and record ECG waveforms, providing users with insights into their cardiac health (31). Smart wristbands and patches are also available in the market, offering ECG monitoring capabilities. These devices are designed to beworn on the wrist or attached to the body, allowing continuous ECG monitoring, and other wearable devices, such as intelligent three-lead electrocardiograph monitors, have been developed to provide ECG monitoring with feedback functions for warning potential heart attacks (32). Patches with embedded electrodes have the ability to wirelessly transmit and record ambulatory ECG data for longer periods of time than a standard Holter. They offer details on the heart rate, pauses, high grade atrioventricular block, counts of isolated supraventricular and ventricular ectopic beats, and runs of supraventricular and ventricular tachycardia (Table1). The Zio Patch (iRhythm Technologies, Inc. San Francisco, UnitedStates), a leadless electrocardiographic monitoring device, has been evaluated in 26,751 consecutive patients for its effectiveness in detecting arrhythmias. The findings could have significant implications for device selection, monitoring duration, and care pathways for arrhythmia evaluation and AF surveillance (33). ePatch is a lightweight, body-worn sensor that records and stores heart rhythm data, which can bedownloaded and evaluated by cardiac monitoring professionals (34). A novel study evaluated the performance of a medical wearable, Everion ® (Biovotion AG, Switzerland), using passive PPG technology for AF detection in patients with paroxysmal or persistent AF during inpatient conditions (Figure2C). Reliable and continuous monitoring of AF by employing a deep neural network demonstrated a 95.2% sensitivity and a 92.5% sensitivity (28). A prospective clinical trial compared the performance of a 14-day continuous electrocardiogram patch (EZYPRO®, Sigknow Biomedical Co., Ltd., Taipei, Taiwan) for detecting arrhythmias compared to conventional 24 h monitoring. The patch was associated with higher detection rates in patients with SVT, irregular SVT without P wave, AF/AFL, and critical arrhythmias (35). The KoMaWo configuration (SmartMedics, Poland), a new variation of ECG electrode positioning, has been tested on 15 patients with ST segment deviations due to coronary artery disease, offering extended monitoring and increased diagnostic accuracy for cardiac arrhythmias, making them a viable alternative to traditional cardiac monitoring methods (36). Numerous devices are available for health monitoring, including the Apple Watch (Apple Inc., Cupertino, CA, UnitedStates), which incorporates accelerometer and PPG-based technologies for heart rate tracking and arrhythmia detection. Smartphone accessories like KardiaMobile (Mountainview, CA), Preventicus (Preventicus ® , Jena, Germany), and Pulse-Smart (Medicore Co., Ltd. in South Korea) use PPG technology to detect arrhythmias and heart rate using touchpad electrodes (37). The Cardiio Rhythm smartphone PPG application (Cardiio Inc., Cambridge, UnitedStates) has provided an accurate and reliable means to detect AF in patients at risk of developing AF, potentially enabling population-based screening for AF (38). Other accurate blood pressure monitoring devices include a small sensor attached to a smartphone, a pressure sensor worn continuously over the wrist, and a system that incorporates both SCG and BCG technology through a chest patch and wrist watch (39). A vest with built-in sensors, electrode connections, and an optical probe clipped on the ear can monitor heart rate, oxygen saturation, and activity levels, as well as dynamic changes in cardiopulmonary function during activity (40). The majority of consumer electronics are heart rate or activity monitors, which can reduce the risk of cardiovascular FIGURE1 Schematic image of developing of the wearable/implantable biosensors in the precision medicine. Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 04 frontiersin.org disease. Wearing pedometers increases daily activity levels, decreases BMI, and lowers blood pressure (41). Mobile apps and wearable devices have been shown to lead to greater weight loss in obese patients (42). In addition, there are several other examples of intermittent atrial fibrillation detection tools used in clinical and research settings including MyDiagnostick (Applied Biomedical Systems BV, Maastricht, Netherlands), Zenicor-ECG, and FibriCheck (Qompium, Hasselt, Belgium). The MyDiagnostick and Zenicor-ECG are commercially available single-lead electrocardiograph devices for AF detection with high sensitivity and specificity (Figure A) (43, 44). FibriCheck is an FDA-cleared photoplethysmography-based smartphone application for heart rate measurement and AF identification (25). Wearable devices are widely used for disease screening, particularly in detecting arrhythmias. The Apple Heart Study found that the Apple Watch can detect asymptomatic atrial fibrillation (Afib) using PPG technology (45). These devices can also help in risk stratification patients with known cardiovascular diseases by tracking vitals and activity levels. These devices significantly impact decision-making and help patients make informed decisions such as Galaxy Watch Active 2, Simband, and AliveCor’s KardiaBand (Figure2D) (26, 27). In addition to disease prevention and screening, these technologies can also help in change management. For instance, a patient experienced ST depressions on their Apple Watch, which can alert them to arrhythmias and ischemia (46). Electrode technology has shown promise in detecting ischemia, as demonstrated in a study involving 200 patients with suspected STEMI symptoms. The study used smartphone-derived ECGs, Livecore, attached to an iPod Touch, and found a good correlation between the two. Overall, ischemia detection using Livecore can berelatively reliable (47). Another study involving 45 patients with chronic heart failure found that seismocardiography chest patch technology can differentiate between compensated and decompensated heart failure states. Although not widely used, these technologies have great potential in providing better care for patients (48). Research on using wearable devices for activity tracking has been used in studies to determine the relationship between post-operative activity and length of stay after major surgeries, including cardiac ECG technology PPG technology III V IV III VI III IIIIV V F A B CDE FIGURE2 Wearable biosensors applications in cardiovascular care. (A) Examples of wearable tools used in clinical settings for ECG monitoring: (I) Fitbit-© Fitbit Inc., San Francisco, CA, United States, all rights reserved. (II) KardiaMobile-© all rights reserved (Mountainview, CA). (III) MyDiagnostick-© Applied Biomedical Systems BV, Maastricht, Netherlands, all rights reserved. (IV) Zenicor-ECG© Zenicor Medical Systems Ltd., London, United Kingdom, all rights reserved. (V) A sample of ECG graph for a healthy heart and, (VI) Afib ECG graph with irregular intervals. (B) Examples of wearable tools for PPG monitoring: (I) anatomical location of fibricheck patch on the chest-© Qompium, Hasselt, Belgium, all rights reserved. (II) Single lead ECG signal and fibricheck PPG signal. Reprinted from reference (25), licensed under CC BY 4.0. (III) Wristband of the Simband with LEDs for PPG and ECG. (IV) A sample 30 s clean PPG segment and corrupted PPG segment collected from Simband. Reprinted from reference (26), licensed under CC BY NC ND. (V) Smartphone camera‐based PPG measurements of the pulse waveform. Reprinted from reference (27), licensed under CC BY 4.0. (C) Recorded PPG and ECG signals with the medical wearable attached to the left upper arm vs. ECG Holter (Everion, Biovotion AG, Switzerland). Reprinted from reference (28), licensed under CC BY. (D) Schematic illustration and image of a soft flexible cardiac sensor in a thin elastic enclosure consisting of the multiple polymeric, electronic, adhesive and hydrogel layers and data transfer to smartphone app (via NFC) for visualization of logged heart rate data and/or real-time ECG waveforms. Reprinted from reference (29), licensed under CC BY. (E) Schematic diagram of a flexible self-powered wearable ECG system. Reprinted from reference (30), Copyright © 2018 American Chemical Society. (F) Zio patch button and placement-© iRhythm Technologies, Inc., San Francisco, United States, all rights reserved. Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 05 frontiersin.org TABLE1 Various device types of wearable biosensors for cardiac function measurements. Device type Manufacturer Product name Cardiac function measurements Other measurements Official website Watch Apple Apple Watch series7 HR, ECG, BP SpO2, fitness tracking, health monitoring features https://www.apple.com/ Watch Galaxy Galaxy Watch Active 2 HR, ECG, BP Spo2, activity tracking, stress management, Health monitoring features https://www.samsung. com/ Watch Garmin Garmin Venu 2/2S HR Blood oxygen levels measuring https://www.garmin. com/ Watch Fitbit Fitbit Sense HR, ECG, HR variability Stress management, activity tracking, Afib assessment https://www.fitbit.com/ Watch WITHINGS Withings ScanWatch HR, ECG, BP SpO2, sleep tracking, activity tracking, breathing disturbances tracking https://www.withings. com/ Watch Amazfit Amazfit GTR 3 HR SpO2, health and activity tracking, sleep monitoring https://www.amazfit. com/ Watch POLAR Polar Vantage V2 HR Fitness and health tracking, Recovery tracking https://www.polar.com/ Wristband Fitbit Fitbit Charge 5 HR, ECG, HR variability Health and fitness, sleep tracking https://www.fitbit.com/ Wristband Garmin Vivosmart 4 HR Smart fitness tracking, blood oxygen saturation, energy monitoring https://www.garmin. com/ Wristband WHOOP WHOOP Strap4.0 HR, HR variability Overall cardiac function, guidance for workouts and recovery, sleep tracking https://www.whoop.com/ Wristband Amazfit Amazfit Band 6 HR, HR variability Health and fitness, sleep tracking, blood oxygen measurement https://www.amazfit. com/ Wristband Samsung Samsung Galaxy Fit 2 HR Activity and fitness tracking, sleep tracking https://www.samsung. com/ Wristband POLAR Polar Ignite 2 HR Sleep tracking, guidance for workouts and recovery https://www.polar.com/ en/ignite2 Wristband WITHINGS Withings Move ECG HR, ECG Activity and sleep tracking, early detection AFib https://www.withings. com/ Chest strap Qardio QardioCore HR, ECG, HR variability Fitness tracking, skin temperature, respiratory rate https://www.qardio.com/ Patch VIVALINK VivaLNK ePatch HR, ECG, HR variability Respiratory rate, skin temperature, step count, posture, 3-axis accelerometer https://www.vivalink. com/ Patch BioTel Heart BioSticker HR, ECG Patch SmartCardia SmartCardia 7L Patch HR, ECG Continuous ambulatory monitoring, managing arrhythmias https://www.smartcardia. com/ Patch NUUBO NUUBO Smart Patch HR, ECG Arrhythmia events detecting like atrial fibrillation, tachycardia, bradycardia and others https://www.nuubo.com/ Patch Sigknow Biomedical Co. EZYPRO ECG Arrhythmia detection, stroke prevention (ischemic/secondary), assess the cause of syncope (psychogenic), routine health check-up (early detection and timely treatment), post heart surgery monitoring https://sigknow.com/en/ ezypro/ (Continued) Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 06 frontiersin.org surgery. It can also serve as an endpoint in drug trials, such as nitrates for heart failure patients to improve activity (49, 50). A meta-analysis of digital health interventions, including telemedicine, web-based monitoring, email messaging, mobile phone tracking, text messaging, and monitoring sensors, found that overall outcomes were better in patients who underwent digital health interventions compared to those receiving usual care. Out of the 1,200 patients in the digital health interventions group, about 100 developed events, while 160in the usual care group developed events (51). Digital health interventions appear to have more effect on secondary prevention of cardiovascular diseases and heart failure patients compared to primary prevention. A pilot study showed that the ReDS vest may reduce heart failure readmissions. Fifty patients were admitted for decompensated heart failure and were instructed to wear the vest for 90 days. After 90 days, the readmission rates were compared. The vest significantly reduced heart failure readmissions compared to pre-and post-wear periods. Although not routinely used, the vest could significantly reduce the disease burden and mortality of cardiovascular diseases (52). With the emergence of the Internet of Things (IoT) era, the development of self-powered wearable medical sensors using flexible electronic devices is on-demand. A self-powered wearable electrocardiography (ECG) system was demonstrated, powered by a wearable thermoelectric generator (w-TEG) using body heat. Parametric studies were conducted on the PHS, and the w-TEG structure was optimized. The output power density was over 38 μW/ cm for the first 10 min and 13 μW/cm for 22 h (Figures2E,F) (29, 30). Wearable/implantable biosensors in neurological care By providing valuable insights into the brain’s activities and overall health, wearable biosensors have the potential to enhance diagnostics, improve treatment outcomes, and enable personalized care for individuals with neurological conditions (53). In this section, wewill explore the significant role of wearable biosensors in neurological care and their potential to transform the way weunderstand and manage neurological disorders. The brain sends command prompts through the spinal cord, but the connection between the brain and the body can bebroken due to physical injury or degenerative disease. The brain computer interface (BCI) can function as a bridge to bypass this broken connection. Existing BCI technology can be categorized into invasive and non-invasive (Figure3A) (57). The Utah Array, the current industry standard, is a TABLE1 (Continued) Device type Manufacturer Product name Cardiac function measurements Other measurements Official website Patch iRhythm Technologies Zio Monitor HR, ECG Detecting different types of arrhythmias, plus sinus rhythm and artifacts https://www.irhythmtech. com/ Smart accessory WITHINGS BPM Core BP, EKG Advanced cardiac health monitoring, detecting masked hypertension, and manage nocturnal hypertension https://www.withings. com/ Smart accessory AliveCor KardiaMobile HR, EKG Detect atrial fibrillation, Bradycardia, and Tachycardia https://alivecor.com/ Smart accessory OMRON Healthcare Omron HeartGuide BP Daily activity tracking, sleep tracking, providing a comprehensive view of heart health https://omronhealthcare. com/ Smart accessory Empatica Embrace2 HR Electrodermal activity, providing insights into stress, detecting possible convulsive seizures https://www.empatica. com/embrace2/ Smart accessory Pulseon PulseOn HR HR, ECG Asymptomatic arrhythmias detection, long-term monitoring of arrhythmias, e.g., atrial fibrillation (AF) www.Pulseon.com Smart accessory Bittium Bittium Faros 360 HR, ECG Sports and medical monitoring, intelligent arrythmia detection https://www.bittium. com/ Smart accessory Komodo Tec AIO Smart Sleeve HR variability, ECG, EKG SpO2, respiration rate monitoring, activity intensity https://komodotec.com/ product/aio-sleeve/ Smart accessory Oura Oura ring HR SpO2, skin temperature, sleep tracking https://ouraring.com Smart accessory toSense CoVa 2 HR, HR variability, ECG, strokevolume, cardiac output Chest fluids, respiratory rate https://www.tosense.com Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 07 frontiersin.org square computer chip with spikes that can read electrical signals from the cortex region of the brain. This process allows a person with a brain implant to control electronic devices with their brain, such as robotic limbs or computers. However, this method is limited to medical research environments (58). The next generation of BCI technology, led by startups like Synchron, Blackrock Neurotech, and Neuralink, could potentially become life-changing medical technology for paralyzed individuals in the near future. Blackrock’s device is implanted directly into the brain (Figure3C), while Synchron’s is implanted into blood vessels in the brain (Figure 3B). Blackrock Neurotech’s BCI the NeuroPort, uses a series of tiny brain chips, called NeuroPort arrays which consist of 96 densely packed electrodes to record and stimulate neurons with high precision from virtually anywhere on the brain surface. Multiple arrays can beplaced in one person, creating braincomputer interfaces and neuroprosthetics that can control objects and repair senses. The signals are transmitted wirelessly to an outside device like a wheelchair or cursor, giving people control over their environment (55). Blackrock has also partnered with the University of Pittsburgh’s rehab neural engineering labs to create the first portable brain computer interface, allowing patients to participate in research trials (69). Neuralink, a founding company, plans to implant electrodes directly into people’s brains, potentially providing a cure for neurological disorders like spinal cord injury, seizures, paralysis, and depression. The Neuralink device, resembling a small coin, uses a robotic sewing machine to insert fine and flexible electrode wires into the outer cortex layer. This device could beused to operate robots, cure paralysis, treat mental illness, stream music, and extend hearing range beyond normal frequencies. The Neuralink device resembles the Utah array and could potentially cure neurological disorders (56). In mid-2021, ClearPoint Neuro and Blackrock Neurotech collaborated to develop an automated surgical solution for placing brain computer interface devices in patients with neurological disorders like paralysis, ALS, and hearing loss (Figure3D) (67). Additionally, ClearPoint has partnered with Higgs boson health to launch a digital patient-facing application using the Manage My Surgery platform, focusing on drug delivery to the spine and brain, as well as BCI technology (Figure3E) (70). BrainGate researchers have demonstrated the first human use of a high bandwidth wireless brain computer interface with an external wireless transmitter, allowing users to operate external devices like computers and robotic arms with their minds. Initial clinical research demonstrated the system’s ability to intuitively control advanced prosthetic limbs and robotic devices, providing paralysis patients with simple control, powerful assistive movement, and communication devices. The ultimate goal is for people to take the device home and use it for daily activities. This research aims to improve independence, mobility, and safety for blind people (Figure3F) (59). Electrocorticography (ECoG) is a non-invasive procedure that uses electrodes placed directly on the brain, allowing for better and more precise signals. It has a higher spatial resolution of approximately 4 square millimeters, making analysis more complex. ECoG grids consist of small disk-like electrodes placed epidurally or subdurally, and the distance between electrodes can vary depending on the region of interest (71). Epilepsy patients with ECoG are often observed for several days or weeks to identify epileptogenic zones, providing a unique opportunity to study electric activity at high spatial and temporal resolution (72). Recent advances allow for long-term or chronic placement of ECoG sensors, enabling the development of ECoG-based brain computer interfaces and closed-loop approaches (73). ECoG can also beused to control prosthetics, recording movement planning signals from the motor cortex and translating them to actual movement of an artificial arm or hand (74). EEG or EMG can beused to control robots and smart devices, such as prosthetics. The Walk Again Project has demonstrated the use of EEG-controlled exosuits to help people walk again, using motor-imagery patterns as triggers to move the robot’s legs (Figure3M) (65). Mind-controlled wheelchairs provide basic directional control using motor imagery, p300 signals, or population encoding (75). CTRL labs developed a wristband that accurately maps finger actuation and hand positioning using electromyographic signals and accelerometer data (76). Several companies are working on developing novel EEG based BCI electrodes interpreting neural activity using artificial intelligence, allowing users to control objects with their minds (77, 78). In a more recent study, a digital bridge between the brain and spinal cord was developed based on the brain-spine interface (BSI) implant to restore communication between the brain and the spinal cord, allowing individuals with chronic tetraplegia to walk naturally in community (79). Traditional BCIs have often utilized rigid electrodes, which, while effective in capturing neural signals, have faced challenges in terms of long-term use and patient comfort. The transition to flexible electrodes marks a significant advancement, addressing these concerns and opening up new possibilities for interfacing with the brain, highlighting significant benefits including enhanced comfort and biocompatibility, improved signal quality, versatility in placement, and long-term stability. Several promising reports are published on the applications of flexible BCI systems in health-related fields such as neuroprosthetics, neurorehabilitation, and cognitive enhancement (Figures3H–K) (60–63). A cutting-edge development in the realm of BCI systems is the emergence of portable, wireless, weakly-invasive BCIs that not only push the frontiers of performance but also enhance user convenience and accessibility. The convergence of portability, wireless connectivity, and weakly-invasive design in BCIs heralds a new era of humancomputer interaction. As these systems evolve, they promise to redefine our relationship with technology, offering not only enhanced capabilities but also a glimpse into the profound possibilities of the human mind (Figure2A) (54, 66, 80). In 2013, Nicolelis and a team of researchers developed the first brain-to-brain interface (BTBI), enabling lab rodents to share sensorimeter information and work together for rewards (81). The BraiNet project connected the brains of three primates, allowing them to move an arm over a target in digital 3D space (82). BCI applications focus on total levels of brain activity and frequency bands, and are used for meditation, focus, and sleep enhancement. Neurofeedback technology changes cues based on brain indicators, such as wakefullness, and is used for meditation, sleep, focus, and seizure monitoring (83). A team of researchers developed a way for disabled artists to create art using a brain computer interface (84). The Neuracle NeuSenW is a fast, small, lightweight, compact, flexible, and wearable system that can transmit up to 64 channels of high-quality EEG wirelessly at up to 16 kilohertz per channel. This system is robust for ambulatory use in naturalistic environments and allows high-accuracy synchronization across multiple devices (85). BIOSEMI, Cognionics, ANT Neuro, G. Tec, Brain Products, and EMOTIV are among the most common EEG-based electrodes mobile systems used to study the neural control of human locomotion (86). A speech neuroprosthetic device was developed by researchers at the University of California San Francisco, which can decode full words and sentences from brain Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 08 frontiersin.org signals of participants who have been unable to speak due to a traumainduced stroke. The device is placed over motor areas associated with speech and can decipher between words in a predetermined set and construct sentences. Data was collected from an electrocorticography array, semi-invasive, paper-thin grids of flat, circular electrodes placed underneath the skull but on top of the brain (87). Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, affecting millions worldwide. Diagnosing PD can bechallenging due to its diverse symptoms and similarities with other illnesses (88). Wearable brain implants have gained attention as valuable tools for managing PD, providing continuous monitoring and objective measurements of motor symptoms. Sensor-equipped wearable devices have shown significant potential in improving early diagnosis and monitoring of PD (89). One notable application of wearable brain implants in PD is the development of an Internet of Things (IoT) platform, pioneered by the Michael J. Fox Foundation for Parkinson’s Disease Research and Intel Corporation (90). Exopulse researchers have developed a suit called Mollii, which uses neuromuscular electrical stimulation to correct muscle tremors caused by degenerative brain disorders. This technology can effectively treat conditions like Parkinson’s, Cerebral Palsy, Spasticity, Multiple Sclerosis, and Chronic Pain (91). Deep brain stimulation (DBS) is FDA-approved for Parkinson’s disease and epilepsy, and has a humanitarian device exemption for dystonia and obsessive-compulsive disorder. There are three FDA-approved DBS therapy devices available: Medtronic, Abot SJM, and Boston Scientific. DBS has been used to treat chronic pain and depression, OCD, as well as other psychiatric disorders like anxiety and PTSD. DBS is like a pacemaker for the brain, improving quality of life by correcting abnormal brain rhythms (Figure3P) (68, 92). Researchers are developing medical devices and AI-driven solutions to improve life for people with Parkinson’s. One such device is the CUE1 non-invasive wearable device, which uses pulsed cueing and focused vibrotactile stimulation to reduce symptoms of slowness and stiffness, resulting in improved movement (93). FIGURE3 Wearable biosensors in neurological care. (A) Top and bottom view of WIMAGINE ECoG recording implant. Reprinted from reference (54), Copyright © 2015, IEEE. (B) Synchron’s Stentrode device expands inside a blood vessel on the brain to relay motor signals. Reprinted from reference (55), licensed under CC BY. (C) Neuralink implants are aimed at enabling human brains to communicate directly with computers. Reprinted from reference (56), © 2024 Springer Nature Limited. (D) Schematic view of the major types of BMI electrode interfaces in brain. Reprinted from reference (57), licensed under CC BY. (E) A 100 microelectrode Utah electrode array and the electrode probe tips implanted into the cortex of brain. Reprinted from reference (58), licensed under CC BY 4.0. (F) The BrainGate neurosensor composed of a silicon-based cortical microelectrode array implanted for intracortical neural microcircuit recording via a percutaneous connection to a skull mounted pedestal connector. Reprinted from reference (59), licensed under CC BY-NC-ND 4.0. (G) The NeuroPort Array chip used by Blackrock Neurotech in its devices. Reprinted from reference (55), licensed under CC BY. (H) Schematic view of a stretchable transparent electrode arrays for simultaneous electrical and optical interrogation of neural circuits in vivo. Reprinted from reference (60), Copyright © 2018 American Chemical Society. (I) Front view and backside of an inkjet printer thin flexible ECoG microelectrode array on a thin parylene-C film. Reprinted from reference (61), licensed under CC BY. (J) Schematic of a PDMS-parylene micro-electrode arrays (MEA) with 10 convex electrode sites in four arms for in vivo ECoG recording from rat olfactory bulb. Reprinted from reference (62), licensed under CC BY. (K) Photo of active area of a silicon carbide array that implanted on primary visual cortex of a rat for electrocorticography and peripheral nerve recording. Reprinted from reference (63), licensed under CC BY 3.0. (L) Electrode fabrication, implantation and in vivo validation of a flexible polymer microECoG array to map functional coherence in schizophrenia model. Reprinted from reference (64), Copyright © 2022, The Author(s) of (64), under exclusive licence to Springer Nature Limited. (M) A soft pneumatic exosuit consisting of two independent elbow sleeves with actuator tubes that snake through the posterior portion of the sleeves to provide flexion assistance. Reprinted from reference (65), licensed under CCD bY. (N) In vivo experimental setup for EMG recording using a neural dust mote was placed on the exposed muscle surface, the external transducer couple’s ultrasound to the mote, and the wireless data are recorded and displayed on the laptop. Reprinted from reference (66), © 2016 Elsevier Inc. (O) Brain-computer interfaces in neurorecovery and neurorehabilitation. Reprinted from reference (67), Copyright © 2021, Rights Managed by Georg Thieme Verlag KG Stuttgart • New York. (P) An illustration of deep brain stimulation for the treatment of Parkinson’s disease. Fine wires are implanted within brain regions involved in motor control, and stimulation is controlled by a pacemaker-like device under the skin. Reprinted from reference (68), Copyright © 2013, © 2013 Wolters Kluwer Health | Lippincott Williams. Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 09 frontiersin.org The next generation of neural implants are being developed at Lawrence Livermore National Laboratory (LLNL) to deepen the exploration of the brain. In collaboration with the National Institute of Health (NIH), University of California San Francisco (UCSF), and other research institutes, engineers are developing brain-based healthcare devices using thin-film micro-electrocorticography surface arrays. These devices can record more information about an individual’s brain state, making treatment more informative and effective (94, 95). This technology is also paving the way for next-generation neural prostheses or implantable devices that could improve the ability of those with disabilities to see, speak, or hear (96, 97). Researchers have developed ultraflexible electrode arrays that can record thousands of neurons in live animals’ brains for months. These recordings enhance decoding accuracy during optogenetic stimulation and enable the detection of strongly coupled neuron pairs, enabling the study of large-scale neural circuits and patterns of information flow (Figure3L) (64). UC Berkeley engineers have developed a wireless, implantable sensor that records electrical signals in nerves, providing real-time data for quadriplegic individuals to use prosthetic limbs. The neural dust used in the device records electrical activity in brain nerve cells, which can beanalyzed to guide prosthetics (Figure3N) (66). Engineers are working on creating a lifetime neural dust implant, which could potentially guide prosthetics and improve the quality of life for individuals with disabilities (98). Wearable biosensors are crucial in neurorehabilitation by enabling continuous monitoring and objective assessment of motor functions and movement patterns. These sensors promote adherence to therapy, monitor progress, and facilitate early intervention, contributing to neuroplasticity and functional recovery. Integrating wearable biosensors in neurological care fosters research and advancements, enabling population-scale studies to identify patterns, risk factors, and potential interventions for neurological disorders (99). Wearable/implantable wearable biosensors in ocular diseases Ocular wearable contact lenses are a promising technology for non-invasive point-of-care testing and monitoring of various ocular diseases. These lenses make direct contact with ocular surfaces and are integrated with electronic devices and biosensors to detect biomarkers within the eye. These devices offer continuous and long-term measurement capabilities, enabling patients to manage their symptoms effectively and conveniently (100). The eye, being a complex sensory organ, contains abundant information that can beharnessed for wearable healthcare platforms. Ocular wearable devices, such as smart contact lenses or glasses, are designed to integrate biosensors that can measure various parameters related to ocular health. These biosensors can detect and monitor biomarkers in tears, enabling the assessment of physiological and pathological conditions (101). Tears provide a direct connection to the blood and exhibit close correlations between tear and blood biomarker concentrations, allowing for the analysis of tear fluid as a non-invasive means of evaluating ocular health. Ocular wearable biosensors can detect specific biomolecules, such as proteins, enzymes, and metabolites, in tears, providing insights into ocular disease states. The analysis of tears offers potential for diagnosing ocular diseases, including conditions such as dry eye syndrome, glaucoma, and ocular inflammation (102). Smart contact lenses offer noninvasive real-time detection of the human body for biomedical information. However, accurate measurement of physiological signals in tears is challenging. A selfpowered multiplexed sensor based on organic electrochemical transistors (OSCs) was demonstrated, allowing semilog-linear response to glucose and calcium ions in tear fluids (103). Another interesting study represented a fluorescent scleral lens sensor was also developed based on a handheld ophthalmic readout device and a smartphone camera for quantitative measurements of physiological levels of pH, Na + , K + , Ca 2+ , Mg 2+ , and Zn 2+ ions in point-of-care settings (104). A soft contact-lens biosensor (SCL-biosensor) was fabricated and tested for non-invasive biomonitoring of tear fluids, showing excellent correlation between output current and glucose concentration (105). A human pilot trial demonstrated that a novel soft, smart contact lens based on a graphene field-effect transistor sensor had a suitable sensitivity for real-time cortisol concentration detection in tears using a smartphone with a low detection limit (106). Recently, exosomes have gained attention as a valuable source of disease biomarkers. A poly (2-hydroxyethyl methacrylate) contact lens with antibody-conjugated signaling microchambers (ACSM-PCL) has been developed to detect tear exosomes that can detect exosomes in various solutions, including regular buffer, cell culture media, and human tears. The ACSM-PCL is expected to bea next-generation smart contact lens for cancer pre-screening and supportive diagnosis (Figure4A) (107). Several biochemical or biophysical sensors have been integrated into contact lenses for detecting single biomarkers in tear fluids, eyeball movement, and mechanical deformation. Wearable contact lenses monitor physiological parameters, but previous sensors only detect one analyte at a time. A multifunctional sensor was developed on an actual ocular contact lens using graphene and metal nanowires for measuring glucose levels in tears and intraocular pressure, evaluated in in-vivo and in-vitro tests using rabbit and bovine eyeballs. This system enables continuous, noninvasive monitoring of physiological conditions and biomarkers related to ocular and other diseases (114). Microfluidics technology has been used to create contact lens sensors that can identify substances in tears, such as glucose, pH, nitrite, proteins, and ascorbic acid, through multiple sensing channels. A study demonstrated the integration of paper microfluidics in laserinscribed contact lenses for multiplexed detection of clinically relevant analytes, such as hydrogen ions, proteins, glucose, nitrites, and L-ascorbic acid. This device has potential for medical diagnosis, disease screening, and monitoring of ocular infections, uveitis, diabetes, keratopathies, and oxidative stress (Figure 4B) (108). Microfluidic contact lenses have also been developed as wearable platforms for in situ tear pH, glucose, protein, and nitrite ions sensing. A microchannel was inscribed using CO 2 laser ablation, and biosensors were embedded within microcavities that responded within 15 s, yielding high sensitivities in detection of pH, glucose, proteins, and nitrites. These contact lens sensing platforms could provide on-eye tears screening and monitor ocular health in clinics and point-of-care settings (115). Evaporation, humidity, tears, and rain can affect eye concentration levels uncorrelated to blood concentration variation. Measurement in the tear film is insufficient for accurate electrochemical measurements and useful diagnostic conclusions. Electrochemical smart contact lenses (ESCL) have been developed to monitor chemical markers Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 16 frontiersin.org rapidly, with a 10% reduction after 3 days and a 30% reduction at 30 days. This is a significant step forward in cancer treatment, and it is hoped that treating cancer will soon beas easy as putting on a hat (194). Envoy Medical’s Acclaim® cochlear implant is an investigational device aimed at improving hearing for adults with moderate to profound sensorineural hearing loss. If approved by the FDA, it would bethe first cochlear implant without external components, ensuring no loss or damage. The implant uses novel sensor technology from Envoy Medical’s Esteem osseointegrated active middle ear implant (AMEI), which was FDA-approved in 2010 (195). Advanced endoscopes with imaging and therapy capabilities offer advantages but lack spatial resolution for diagnosing and treating small cancers. A multifunctional endoscope-based interventional system combines transparent bioelectronics with theranostic nanoparticles, enabling optical fluorescence-based mapping, electrical impedance and pH sensing, contact/temperature monitoring, radio frequency ablation, and localized photo/chemotherapy. This technology is useful for accurate detection, delineation, and targeted therapy of colon cancer, treating chronic inflammatory bowel diseases, and enhancing tumor detection accuracy (196). Researchers have developed Pillsense, a swallowable device that detects gastrointestinal bleeding using a fluorescence detector. The world’s smallest floor imager, it uses an LED, lens, optical filter, and excitation filter. This innovative solution could prevent gastrointestinal bleeding in pre-symptomatic individuals without displaying symptoms (197). There is a significant opportunity in the field of biometric sensors, which offer various modalities, form factors, and insights. Selfpowered capabilities can beconfigured for some of these technologies, but further advancements are needed in sensing mechanisms. Examples include injectable biometric sensors for photoplethysmography, accelerometry, and thermometry (198), battery-free wireless ultrasonic sensors like endoleak sensing in aortic valves (199), and cardiac stem cells patched on the heart powered by ultrasound (200). Transdermal and breath biomarker sensing can detect body conditions like metabolic states or COVID-19 infection (201). Startups like NEXT system, ClearSense, Everactive, Dermisense, VitaFlo, Onda Vision, and Olftech are actively pursuing technology development. Future opportunities include new energy harvesting modes, non-invasive sensing modalities like heat flux sensors, blood pressure sensors, artificial intelligence, and machine learning. Additionally, reconfigurable sensor systems can beused to change the sampling rate or sensing target based on context. Conclusion While the integration of precision medicine and wearable biosensors holds immense promise, several challenges must beaddressed. These include issues related to data privacy, the need for standardized data formats, and the importance of educating both healthcare providers and the general public about the potential benefits and limitations of these technologies. The integration of biosensors into everyday life presents challenges, including the need for wearable devices to becomfortable, unobtrusive, and fashionably acceptable, and implantables to navigate biocompatibility and longterm stability. Accuracy and reliability of biosensor data are crucial for clinical utility, and bridging gaps between medical, engineering, and data science disciplines is essential. Ethical concerns regarding privacy, consent, and data ownership are crucial for the widespread acceptance and ethical deployment of biosensors in precision medicine. Future biosensors may leverage advancements in sensing technologies, such as nanoscale sensors and innovative biomaterials, to enhance the specificity and sensitivity of biosensors. Integrated health platforms that combine data from wearable and implantable biosensors with electronic health records could provide healthcare professionals with a comprehensive view of a patient’s health, facilitating more informed and personalized treatment strategies. Predictive analytics and artificial intelligence are key to extracting meaningful insights from biosensor data, with machine learning algorithms aiding in identifying patterns, predicting disease trajectories, and optimizing treatment plans. As technology evolves, there is a growing potential to empower individuals to actively participate in their healthcare, fostering health literacy and self-management. In conclusion, while challenges persist, the future prospects of wearable and implantable biosensors in precision medicine are promising. Addressing current obstacles through collaborative efforts and embracing technological advancements could pave the way for a healthcare landscape where personalized interventions based on realtime, accurate data become the standard rather than the exception. Author contributions EG: Writing – original draft. ZN: Writing – review & editing. H-PD: Conceptualization, Writing – review & editing. HR: Validation, Visualization, Investigation, Writing – review & editing. ZA: Resources, Conceptualization, Writing – review & editing. Funding The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by the Alexander von Humboldt Foundation. Acknowledgments The authors acknowledge the support of the Alexander von Humboldt Foundation for EG via the Post-Doctoral Research Fellowship. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could beconstrued as a potential conflict of interest. Ghazizadeh et al. 10.3389/fmed.2024.1390634 Frontiers in Medicine 17 frontiersin.org Publisher's note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may beevaluated in this article, or claim that may bemade by its manufacturer, is not guaranteed or endorsed by the publisher. References 1. Naithani N, Sinha S, Misra P, Vasudevan B, Sahu R. Precision medicine: concept and tools. Med J Armed Forces India. (2021) 77:249–57. doi: 10.1016/j.mjafi.2021.06.021 2. Mirnezami R, Wafi A. Chapter 54—the future of precision medicine In: J Faintuch and S Faintuch, editors. Precision medicine for investigators, practitioners and providers. 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