Wearable Devices Research Articles

High-Performance Triboelectric Nanogenerator Based on Silk Fibroin-MXene Composite Film for Diagnosing Insomnia Symptoms.

In this study, we developed a flexible, biocompatible, and high-output electrical performance triboelectric nanogenerator (TENG) employing a silk fibroin (SF)-MXene composite film (SF-MXene-F) and a PDMS film as the friction layer. The inclusion of MXene in the SF film increased its surface charge density, presenting a practical approach to designing high-performance SF composite film-based TENGs. At a MXene content of 40%, our SF-MXene composite film-based TENG (SF-MXene-FTENG) achieved optimal output electrical performance, featuring a maximum open-circuit voltage (Voc) of 418 V, a maximum short-circuit current (Isc) of 11.6 μA, and a maximum output power density of 9.92 W/m2. The Voc and power densities of the SF-MXene-FTENG surpassed previously reported optimal values for SF-based TENGs by 1.6 and 3.8 times, respectively. Furthermore, leveraging the exceptional biocompatibility and light shading performance of TENGs, we designed a wearable smart TENG eye mask capable of diagnosing insomnia symptoms and monitoring sleep quality in real time. The SF-MXene-FTENG holds promising application potential as a wearable electronic device for diagnosing sleep-related diseases.

Ultrasensitive and Stretchable Strain Sensors Based on Laser-Induced Graphene With ZnO Nanoparticles.

Laser-induced graphene (LIG) has attracted considerable attention for its use in flexible and stretchable sensors, owing to its electrical/mechanical properties and scalable fabrication processes. Although laser scanning facilitates the formation of LIG and its strain sensor, the strain-sensing sensitivity enhancement of LIG remains limited by the material's properties and structural design. In this study, we demonstrate a substantial improvement in sensitivity that was achieved by fabricating a LIG using ZnO nanoparticle (NP)-assisted photothermal enhancement. The results show that ZnO NPs selectively reduce the threshold fluence needed to convert polyimide (PI) into LIG. By transferring the LIG formed on PI to poly(dimethylsiloxane), we fabricate a stretchable strain sensor with ultrahigh sensitivity and a gauge factor of 1214 at 10% strain, which is approximately 60 times higher than the gauge factor without ZnO NPs. Using the selective graphenization properties of LIG, a flexible, dual-sided integrated sensor sheet that is equipped with flexible strain and ultraviolet (UV) sensors is demonstrated. This sheet enables simultaneous monitoring of UV intensity and joint bending angles of sports wearable devices. We validated the developed sensors by attaching them to a runner's body to monitor and simulate forefoot and heel strikes, demonstrating the sensor's ultrahigh sensitivity and long-term stability without the need for a camera. These findings highlight the potential of the proposed method for developing multifunctional sensor applications with ultrahigh sensitivity and stability.

Alphabet Handwriting Recognition: From Wood-Framed Hydrogel Arrays Design to Machine Learning Decoding.

Handwriting recognition is a highly integrated system, demanding hardware to collect handwriting signals and software to deal with input data. Nonetheless, the design of such a system from scratch with sustainable materials and an easily accessible computing network presents significant challenges. In pursuit of this goal, a flexible, and electrically conductive wood-derived hydrogel array is developed as a handwriting input panel, enabling recognizing alphabet handwriting assisted by machine learning technique. For this, lignin extraction-refill, polypyrrole coating, and polyacrylic acid filling, endowing flexibility, and electrical conduction to wood are sequentially implemented. Subsequently, these woods are manufactured into a 5×5 array, creating a matrix of signals upon handwriting. Efficient handwritten recognition is then achieved through appropriate manual feature extraction and algorithms with low complexity within a computing network, as demonstrated in this work, the strategic choice of expertise-based feature engineering and simplified algorithms effectively boost the overall model performance on handwriting recognition. With potential adaptability, further applications in customized wearable devices and hands-on healthcare appliances are envisioned.

The behavioral and physiological correlates of affective mood switching in premenstrual dysphoric disorder

Premenstrual dysphoric disorder (PMDD), a more severe manifestation of premenstrual syndrome (PMS), is characterized by emotional, behavioral, and physical symptoms that begin in the mid-to-late luteal phase of the menstrual cycle, when estradiol and progesterone levels precipitously decline, and remit after the onset of menses. Remotely monitoring physiologic variables associated with PMDD depression symptoms, such as heart rate variability (HRV), sleep, and physical activity, holds promise for developing an affective state prediction model. Switching into and out of depressive states is associated with an increased risk of suicide, and therefore, monitoring periods of affective switching may help mitigate risk. Management of other chronic health conditions, including cardiovascular disease and diabetes, has benefited from remote digital monitoring paradigms that enable patients and physicians to monitor symptoms in real-time and make behavioral and medication adjustments. PMDD is a chronic condition that may benefit from real-time, remote monitoring. However, clinical practice has not advanced to monitoring affective states in real-time. Identifying remote monitoring paradigms that can detect within-person affective state change may help facilitate later research on timely and efficacious interventions for individuals with PMDD. This narrative review synthesizes the current literature on behavioral and physiological correlates of PMDD suitable for remote monitoring during the menstrual cycle. The reliable measurement of heart rate variability (HRV), sleep, and physical activity, with existing wearable technology, suggests the potential of a remote monitoring paradigm in PMDD and other depressive disorders.

Optimization of Thermoelectric Performance of Ag2Te Films via a Co-Sputtering Method.

Providing self-powered energy for wearable electronic devices is currently an important research direction in the field of thermoelectric (TE) thin films. In this study, a simple dual-source magnetron sputtering method was used to prepare Ag2Te thin films, which exhibit good TE properties at room temperature, and the growth temperature and subsequent annealing process were optimized to obtain high-quality films. The experimental results show that films grown at a substrate temperature of 280 °C exhibit a high power factor (PF) of ~3.95 μW/cm·K2 at room temperature, which is further improved to 4.79 μW/cm·K2 after optimal annealing treatment, and a highest PF of ~7.85 μW/cm·K2 was observed at 200 °C. Appropriate annealing temperature effectively increases the carrier mobility of the Ag2Te films and adjusts the Ag/Te ratio to make the composition closer to the stoichiometric ratio, thus promoting the enhancement of electrical transport properties. A TE device with five legs was assembled using as-fabricated Ag2Te thin films. With a temperature difference of 40 K, the device was able to generate an output voltage of approximately 14.43 mV and a corresponding power of about 50.52 nW. This work not only prepared a high-performance Ag2Te film but also demonstrated its application prospects in the field of self-powered electronic devices.

Development of Ultrathin, Breathable, Waterproof, and Durable Nanonet‐Supported Ionogel Sensors for Electrophysiological Monitoring

AbstractIonogel has gained attention as a promising material for flexible electronic skin (e‐skin), due to its exceptional conductivity, compositional stability, and biocompatibility. Nevertheless, establishing a seamless interface between ionogel and human skin remains a significant challenge. This study presents the design and fabrication of a nanonet‐supported ionogel with a thickness of ≈16 µm, marking it the thinnest ionogel reported to date. This ultrathin ionogel exhibits remarkable toughness (5.51 MJ m−3), a broad strain range (0–375%), and impressive fatigue resistance, enduring over 3000 cycles. Additionally, it offers excellent water resistance and a high water vapor transmission rate (WVTR), supporting perspiration and enhancing skin breathability. Moreover, the ultrathin ionogel has potential as a carrier in transdermal drug delivery systems (TDDS), highlighting its suitability for biomedical applications. Wearable devices incorporating this ultrathin ionogel facilitate continuous, sensitive, and highly accurate monitoring of physiological signals, positioning it as a promising material for future flexible e‐skin material.

Humidity Sensing Using Polymers: A Critical Review of Current Technologies and Emerging Trends

In the post-pandemic era, human demand for a healthy lifestyle and a smart society has surged, leading to vibrant growth in the field of flexible electronic sensor technology for health monitoring. Flexible polymer humidity sensors are not only capable of the real-time monitoring of human respiration and skin moisture information but also serve as a non-contact human–machine interaction method. In addition, the development of moist-electric generation technology is expected to break free from the traditional reliance of flexible electronic devices on power equipment, which is of significant importance for the miniaturization, reliability, and environmentally friendly development of flexible devices. Currently, flexible polymer humidity sensors are playing a significant role in the field of wearable electronic devices and thus have attracted considerable attention. This review begins by introducing the structural types and working principles of various humidity sensors, including the types of capacitive, impedance/resistive, frequency-based, fiber optic, and voltage-based sensors. It mainly focuses on the latest research advancements in flexible polymer humidity sensors, particularly in the modification of humidity-sensitive materials, sensor fabrication, and hygrosensitivity mechanisms. Studies on material composites including different types of polymers, polymers combined with porous nanostructured materials, polymers combined with metal oxides, and two-dimensional materials are reviewed, along with a comparative summary of the fabrication and performance mechanisms of related devices. This paper concludes with a discussion on the current challenges and opportunities faced by flexible polymer humidity sensors, providing new research perspectives for their future development.

Intelligent assistive obstacle avoidance device based on SLAM and wearable technology

Abstract. This paper presents a conceptual design for an intelligent assistive device that combines visual simultaneous localisation and mapping (SLAM) with wearable technology. The device has been developed through the integration of two innovative fields: visual SLAM and wearable technology. The objective is to develop a device that is both user-friendly and safe. The design addresses the issue of safety for visually impaired individuals when they are outside the home. The objective is to provide a dependable, real-time, and resilient solution that can be utilised in intricate indoor and outdoor settings. The system is designed to provide reliable, real-time, and highly effective solutions in variable environments. The main components of the proposed system include visual SLAM, intelligent wearable devices (as carriers), and a comfortable and straightforward user feedback system (through haptic, auditory, or visual signals to provide feedback to the wearer), while simultaneously considering the safety and comfort of the device. This is due to the consideration of the prolonged and frequent periods of use by visually impaired individuals. This paper considers the latest advances in SLAM algorithms, improvements in wearable sensors and the latest developments in robotics for assisting visually impaired people. It also discusses the potential of these technologies in the future development of assistive devices. The aim is to provide a feasible, comfortable and safe solution that will enhance the safety and autonomy of visually impaired people when they are outside.

Effects of using wearable devices on reducing sedentary time and prolonged sitting in healthy adults: a network meta-analysis

ObjectivesThis study aimed to compare the effectiveness of different wearable intervention strategies in reducing sedentary time (ST) and prolonged sitting (PS) on healthy adults.DesignA network meta-analysis (NMA).Data sourcesPubMed, Web of Science, SPORTDiscus, ProQuest, Opengrey, Medline and Cochrane Central Register of Controlled Trials were searched up to 1 June 2024.Eligibility criteria for selecting studiesRandomised controlled trials (RCTs) that examined the effect of wearable device interventions on ST and PS among healthy adults were included.Data extraction and synthesisTwo independent reviewers used standardised methods to search, screen and code included studies. Bias risks were assessed using Cochrane tools (Risk of Bias 2.0). Data were analysed using a frequentist framework NMA to directly and indirectly compare the effects of the five different intervention strategies (comparators). The results were reported as standardised mean differences (SMDs) with 95% CI and surface under cumulative ranking curve (SUCRA) was used to rank the best interventions. The five comparators were as follows: (1) wearable-only intervention (only using wearable devices for self-monitoring); (2) wearable combined with online intervention (ie, online coaching and social media support); (3) wearable combined with offline intervention (ie, face-to-face seminars and courses); (4) comparison group (ie, traditional, non-wearable interventions); (5) control group (ie, maintaining daily routine, waitlist).Results12 RCTs with a total of 2957 participants were included. Results of NMA showed that the ‘wearable+online’ has significantly better effects in reducing ST compared with control group, comparison group and ‘wearable only’, with moderate to large effect sizes (SMD=0.96, 95% CI 0.65 to 1.27; SMD=0.87, 95% CI 0.21 to 1.53; SMD=0.78, 95% CI 0.14 to 1.42, respectively). However, no significant differences were identified between the groups in reducing PS. The SUCRA values were ranked as wearable+online (98.1%), wearable+offline (64.4%,), ‘wearable only’ (40.5%), comparison group (25.9%) and control group (21.1%) for ST reduction. Similar rankings were observed for PS reduction, with probabilities of 69.9%, 61.1%, 59.7%, 37.1% and 22.1%, respectively.ConclusionsWearable+online is the best intervention strategy for reducing ST in healthy adults. Additionally, none of the wearable-based interventions effectively reduced PS in healthy adults, but as there is little research on PS, it should receive more attention in the future.PROSPERO registration number:CRD42021290017.

Use of commercially available wearable devices for physical rehabilitation in healthcare: a systematic review

ObjectivesTo evaluate whether commercially available ‘off-the-shelf’ wearable technology can improve patient rehabilitation outcomes, and to categorise all wearables currently being used to augment rehabilitation, including the disciplines and conditions under...

Wearable Technology Applications and Methods to Assess Clinical Outcomes in Foot and Ankle Disorders: Achievements and Perspectives.

Foot and ankle disorders are a very common diseases, represent a risk factor for falls in older people, and are associated with difficulty performing activities of daily living. With an increasing demand for cost-effective and high-quality clinical services, wearable technology can be strategic in extending our reach to patients with foot and ankle disorders. In recent years, wearable sensors have been increasingly utilized to assess the clinical outcomes of surgery, rehabilitation, and orthotic treatments. This article highlights recent achievements and developments in wearable sensor-based foot and ankle clinical assessment. An increasing number of studies have established the feasibility and effectiveness of wearable technology tools for foot and ankle disorders. Different methods and outcomes for feasibility studies have been introduced, such as satisfaction and efficacy in rehabilitation, surgical, and orthotic treatments. Currently, the widespread application of wearable sensors in clinical fields is hindered by a lack of robust evidence; in fact, only a few tests and analysis protocols are validated with cut-off values reported in the literature. However, nowadays, these tools are useful in quantifying clinical results before and after clinical treatments, providing useful data, also collected in real-life conditions, on the results of therapies.

Economic impact case study of a wearable medical device for the diagnosis of obstructive sleep apnoea

BackgroundAcuPebble SA100 (‘AcuPebble’) is a novel wearable medical device to diagnose obstructive sleep apnoea (OSA). This paper investigates the potential economic impact of the technology in the UK through cost savings analysis, and the redirection of savings into further diagnoses.MethodsA cost comparison study was conducted, comparing AcuPebble to the standard diagnostic approach of home respiratory polygraphy (HRP) and in-clinic polysomnography (PSG), estimating the net benefit value (NBV) and return on investment (ROI). Cohort size was varied to model the effects of volume discounted pricing and staff training costs. To demonstrate the potential for cost savings, data on the healthcare costs of undiagnosed OSA patients were used to quantify the benefit of increased OSA diagnosis rates, as facilitated by AcuPebble.ResultsFor 500 uses of AcuPebble, the NBV in the diagnostic pathway over one year would be in excess of £101,169, increasing to £341,665 for 1,500 uses, £1,263,993 for 5,000 uses, and to £2,628,198 for 10,000 uses, with ROIs of 2.02, 3.03, 5.05, and 6.56, respectively. Given an initial cohort of 1,500 patients, 4,555 extra AcuPebble studies could be completed by redirecting resources from HRP/PSG. Direct cost savings to the NHS from resultant lower undiagnosed rates could be between £24,147 and £4,707,810, based on the cost per use and the percentage of tests that result in a positive diagnosis (varied from 25 to 75% positives).ConclusionsAcuPebble presents an opportunity for substantial healthcare savings, enabling an increase in the number of people tested, diagnosed and treated for OSA.

Pasteables: A Flexible and Smart “Stick-and-Peel” Wearable Platform for Fitness and Athletics

Wearable technologies are becoming increasingly popular and transforming our fitness and sports industry. Monitoring health parameters and body activity can help achieve fitness goals, improve sports performance, and aid in physiotherapy. However, state-of-the-art wearable devices are often not flexible, expensive, hard to set up, or have privacy concerns. They are designed and optimized for a specific application with tight hardware-software integration and it is hard or impossible to re-purpose them for diverse use cases. In this paper, we propose a flexible, re-configurable human body movement and health monitoring platform, called "Pasteables". It is a stick-and-peel device (which acts like a band-aid) that attaches to the skin or clothing and can create an on-body network of smart wearables. Given an application, Pasteables can be easily adapted to its requirements while ensuring good performance and privacy. We present the overall architecture, system design steps, and the configuration process. We have designed a set of functional prototypes and configured them for performing a variety of camera-less pose and posture detection tasks, which are important for athletes, professional dancing, physiotherapy, and fitness workouts. We note that the Pasteables can perform pose/posture detection without external stationary reference at low cost and high accuracy.

Fabrication and characterization of UV-curable thiol-functionalized siloxane elastomers with enhanced adhesion for flexible substrates

The rapid advancement of flexible and wearable devices has increased the demand for substrate materials with excellent elasticity, biocompatibility, and transparency. Polydimethylsiloxane (PDMS) is widely used in these applications due to its advantageous properties. However, its inherently low surface energy limits its adhesion in high-stretchability contexts. To address this issue, various surface modification techniques have been developed, but these methods often alter the intrinsic properties of PDMS or introduce complexities in the manufacturing process. This study proposes elastomers based on ultraviolet (UV)-curable siloxane resins, which retain outstanding flexibility and transparency while significantly enhancing adhesion properties. UV-curable siloxanes were synthesized to prepare elastomers that were evaluated for their mechanical, thermal, and surface properties in comparison with PDMS. Results indicate that the prepared elastomers can be rapidly cured under UV exposure, achieving storage moduli 6 and 37 times higher than those of PDMS at 25°C and 100°C, respectively. Furthermore, thermal conductivity improved by 60%, and the coefficient of thermal expansion was reduced by 26%, demonstrating superior mechanical stability across diverse conditions. Adhesion properties were also markedly enhanced, as shown by peel-test adhesion strength that was 7 times greater than that of conventional PDMS.

Incorporation of polyvinyl alcohol in bacterial cellulose/polypyrrole flexible conductive films to enhance the mechanical and conductive performance

The integration of polypyrrole (PPy) into bacterial cellulose (BC) has provided significant conductivity and cost benefits. However, this combination has led to a reduction in mechanical properties, particularly in terms of elongation at break and tensile strength. This study investigated the enhancement of BC/PPy composite films by incorporating polyvinyl alcohol (PVA). The resulting BC/PPy/PVA films demonstrated improvements in flexibility, tensile strength and thermal stability. Specifically, with 7 % PVA, the flexible films exhibited remarkable enhancements: tensile strength increased from 11.01 MPa (for BC/PPy) to 25.27 MPa and elongation at break rose from 5.81 % to 11.54 %. Additionally, the electrical conductivity of the BC/PPy/PVA films with a resistance of 38.5 Ω, surpassed that of the BC/PPy films. Furthermore, the equilibrium swelling water absorption rates of BC/PPy and BC/PPy/PVA films were 30.6 % and 81.4 %, respectively, with corresponding resistances of 530 Ω and 540 Ω. The variation in resistance between the dry and swollen states of the BC/PPy/PVA flexible conductive film resulted in differences in the brightness of the small light bulb. These findings highlighted the synergistic effects of PVA within the BC/PPy matrix, presenting a promising avenue for developing high-performance conductive materials suitable for flexible electronics and wearable devices.

Biomimetic Structural Hydrogels Reinforced by Gradient Twisted Plywood Architectures.

Naturally structural hydrogels such as crustacean exoskeletons possess a remarkable combination of seemingly contradictory properties: high strength, modulus, and toughness coupled with exceptional fatigue resistance, owing to their hierarchical structures across multiple length scales. However, replicating these unique mechanical properties in synthetic hydrogels remains a significant challenge. This work presents a synergistic approach for constructing hierarchical structural hydrogels by employing cholesteric liquid crystal self-assembly followed by nanocrystalline engineering. The resulting hydrogels exhibit a long-range ordered gradient twisted plywood structure with high crystallinity to mimic the design of crustacean exoskeletons. Consequently, the structural hydrogels achieve an unprecedented combination of ultrahigh strength (46±3MPa), modulus (496±25MPa), and toughness (170±14MJ m-3), together with recorded high fatigue threshold (32.5kJ m-2) and superior impact resistance (48±2kJ m-1). Additionally, through controlling geometry and compositional gradients of the hierarchical structures, a programmable shape morphing process allows for the fabrication of complex 3D hydrogels. This study not only offers valuable insights into advanced design strategies applicable to a broad range of promising hierarchical materials, but also pave the ways for load-bearing applications in tissue engineering, wearable devices, and soft robotics.

Feasibility of Acoustic Features of Vowel Sounds in Estimating the Upper Airway Cross Sectional Area during Wakefulness: A Pilot Study

Assessment of upper airway dimensions has shown great promise in understanding the pathogenesis of obstructive sleep apnea (OSA). However, the current screening system for OSA does not have an objective assessment of the upper airway. The assessment of the upper airway can accurately be performed by MRI or CT scans, which are costly and not easily accessible. Acoustic pharyngometry or Ultrasonography could be less expensive technologies, but these require trained personnel which makes these technologies not easily accessible, especially when assessing the upper airway in a clinic environment or before surgery. In this study, we aimed to investigate the utility of vowel articulation in assessing the upper airway dimension during normal breathing. To accomplish that, we measured the upper airway cross-sectional area (UA-XSA) by acoustic pharyngometry and then asked the participants to produce 5 vowels for 3 seconds and recorded them with a microphone. We extracted 710 acoustic features from all vowels and compared these features with UA-XSA and developed regression models to estimate the UA-XSA. Our results showed that Mel frequency cepstral coefficients (MFCC) were the most dominant features of vowels, as 7 out of 9 features were from MFCC in the main feature set. The multiple regression analysis showed that the combination of the acoustic features with the anthropometric features achieved an R2 of 0.80 in estimating UA-XSA. The important advantage of acoustic analysis of vowel sounds is that it is simple and can be easily implemented in wearable devices or mobile applications. Such acoustic-based technologies can be accessible in different clinical settings such as the intensive care unit and can be used in remote areas. Thus, these results could be used to develop user-friendly applications to use the acoustic features and demographical information to estimate the UA-XSA.

Construction of Smart Clothing Service System for the Health and Well-Being of the Aging Community in a Sustainable Society

Objective: The phenomenon of global aging is becoming more and more severe, and security services such as nursing and guardianship for the elderly have become the focus of social attention. According to the data released by the World Health Organization, by 2030, one out of every six people will be over 60 years old. By 2050, the world population will be 2.1 billion over 60 years old, and the number of people over 80 years old will reach 460 million. This paper aims to monitor the health and services of aging clothing intelligently for the health and well-being of the aging community in a sustainable society, starting from the physiological and psychological needs of the new elderly. Theoretical Framework: In the age-appropriate smart clothing service system, the critical link is to construct the human-computer interaction mode of clothing and wearable devices, establish a design paradigm from single interaction to multi-interaction, and form a service terminal based on smart wearable. Method: This paper designs an aging smart clothing design system using field research, questionnaires, interviews, etc., analyzes the aging smart wearable clothing evaluation system, and constructs aging smart clothing that meets the actual needs of health and well-being for the elderly in a sustainable society. Results and Discussion: In this research, The results obtained sustainable design theories and methods combined with interdisciplinary research tools as the basis of data analysis from the aging intelligent clothing product design system, age-appropriate smart clothing service system, and age-appropriate smart clothing evaluation system. Research Implications: Population aging has been the basic national condition of our country for quite a long time in the future, and "healthy aging" is a strategic measure put forward by the government around the intelligent care service system for the elderly, communities, and institutions. Important direction. Among them, how to build an age-appropriate smart wearable product service system has become the main development content. Therefore, its intelligence and synergistic combination with terminals such as communities, caregivers, and hospitals will become the trend of smart elderly care. Originality/Value: This study contributes to Construct a systematic design of a new intelligent wearable clothing service system for the elderly, which is a great of significance for improving the service quality index of the health and well-being of the elderly. At the same time, it is of great value to expand and deepen the concept of sustainable design.

MOBILE HEALTH: ECG MONITORING FOR ATRIAL FIBRILLATION DETECTION

This systematic review examines the use of mobile health (mHealth) technologies, such as smartphone apps and wearable devices, for detecting atrial fibrillation (AF). The review includes studies assessing the quality and performance of mobile apps and smartwatch algorithms, as well as the clinical validity of ECG measurement and photoplethysmography technology. Findings suggest diverse results, with some studies indicating promising sensitivity and specificity for AF detection. However, there is a need for further research to develop reliable algorithms for diagnosing and managing cardiovascular conditions using mHealth technologies.

Improving Surgical Outcomes for Older Adults with Adoption of Technological Advances in Comprehensive Geriatric Assessment

Frailty is a well-recognized predictor of poor surgical outcomes for older adults, yet effective measurements and interventions remain limited. Technological advances offer an opportunity to address this gap and improve surgical care for older adults. This paper reviews the background of frailty and comprehensive geriatric assessments in surgery, and how technological innovations can advance frailty measurement and intervention in surgical settings. We review two broad areas of technological advancement as applied to frailty in surgery: 1) Innovation in the use of electronic health records (EHR) using Artificial Intelligence (AI) and Machine Learning (ML), and 2) Novel uses for wearable sensors and mobile health (mHealth) applications. We explore the integration of AI and ML with EHR systems, which can surpass traditional comorbidity indices by providing comprehensive health assessments and enhancing prediction models. Innovations like the electronic Frailty Index (eFI) show promise in expanding the reach of frailty assessments and facilitating real-time screening. Additionally, wearable devices and mobile health (mHealth) applications offer new ways to monitor and improve physical activity, nutrition, and psychological well-being, supporting perioperative rehabilitation. While these technologies present challenges, such as the need for infrastructure, training, and data interoperability, they offer promising strategies to facilitate the assessment and management of frailty among surgical patients. Continued research and tailored implementation strategies will be essential to fully realize the potential of these advancements in improving surgical outcomes for frail older adults.