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Wearable sensors are experiencing vibrant growth in the fields of health monitoring systems and human motion detection, with comfort becoming a significant research direction for wearable sensing devices. However, the weak moisture-wicking capability of sensor materials leads to liquid retention, severely restricting the comfort of the wearable sensors. This study employs a pattern-guided alignment strategy to construct microhill arrays, endowing triboelectric materials with directional moisture-wicking capability. Within 2.25 s, triboelectric materials can quickly and directionally remove the droplets, driven by the Laplace pressure differences and the wettability gradient. The directional moisture-wicking triboelectric materials exhibit excellent pressure sensing performance, enabling rapid response/recovery (29.1/37.0 ms), thereby achieving real-time online monitoring of human respiration and movement states. This work addresses the long-standing challenge of insufficient moisture-wicking driving force in flexible electronic sensing materials, holding significant implications for enhancing the comfort and application potential of electronic skin and wearable electronic devices.

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Establishing a relationship between repetitions left in reserve and the mean absolute velocity (RIR-velocity relationship) during resistance training (RT) could allow for objective monitoring, prescription, and real-time adjustment of the training load and set-volume. Therefore, we examined the goodness of fit and prediction accuracy of general and individual RIR-velocity relationships in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests 72 h apart. We found greater goodness of fit of individual RIR-velocity relationships compared to general RIR-velocity relationships. Individual, but not general RIR-velocity relationships established in the first testing session yielded acceptable prediction accuracy of RIR (mean error <2 repetitions) in the subsequent testing session, regardless of the load used. Similar results were obtained when both general and individual RIR-velocity relationships were averaged across the loads, suggesting that a single RIR-velocity relationship covering a range of loads can be used instead of traditional RT methods, potentially allowing for better fatigue management and more efficient adaptation.

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PURPOSE: This study aimed to quantify the potential variability in the volume of work completed after reaching different velocity loss (VL) thresholds and determine the effects of sex, training status and history, as well as psychological traits on the reliability and magnitude of the amount of work completed after reaching different VL thresholds using different loads in the back-squat exercise. METHODS: Forty-six resistance-trained people (15 females and 31 males; 18 to 40 years of age) with a wide range of strength levels, training experience, and different training practices were recruited and performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min of rest between sets. The Bland-Altman analysis for multiple observations per participant and equivalence tests were used to quantify the variability in the volume of work completed after reaching different VL thresholds, whereas linear and generalised mixed-effects models were used to examine the effects of different moderators on the stability and magnitude of the amount of work completed after reaching different VL thresholds. RESULTS: The findings of the present study question the utility of using VL thresholds to prescribe resistance training (RT) volume as the agreement in the amount of work completed across two consecutive testing sessions was not acceptable. Regardless of the load used, females completed more repetitions than males across VL thresholds, while males performed repetitions at higher velocities. In addition, individuals with higher levels of emotional stability also tended to perform more repetitions across VL thresholds. Finally, sex, choice of load, strength levels and training practices, as well as emotional stability affected the linearity of the repetition-velocity relationship and when sets terminated. CONCLUSION: Using the same VL thresholds for all individuals, while assuming generalisability of the stimuli applied, would likely lead to variable acute physiological responses to RT and divergent neuromuscular adaptations over long term. Therefore, VL monitoring practices could be improved by considering sex, training status, history, and psychological traits of individuals due to their effects on the variability in responses to different VL thresholds.

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Background: Digital health technologies have potential to address the challenges associated with traditional cardiac rehabilitation (CR). However, it is not complete enough for prescribed exercise guidance and remote monitoring. Objective: We aimed to evaluate the feasibility of a smartphone app for prescribed exercise tutoring by exercise videos combined with wearable devices to monitor heart rate in patients with stable coronary heart disease (CHD). Methods: The study is a quasi-experimental design study with a single group. A total of 31 patients were included with an average age of 56.2 years (SD 13.4). They participated in a 12-week remote digital CR program. We employed a wearable heart rate monitoring device connected with an app to monitor the patients' exercise intensity. The app can display the videos corresponding to an exercise prescription to guide the exercise. Cardiorespiratory endurance, blood pressure, blood glucose, cholesterol, blood uric acid, left ventricular ejection fraction and quality of life (QoL) were assessed at the beginning and end of the intervention. Compliance and safety events were recorded as well. Results: Completion rate reached 90.3%. Average daily effective exercise time was 39.4 min (SD 17.8), and 92.9% of the patients could exercise in the prescribed intensity for at least 20 min per day. Average effective exercise days per week were 4.6 days (SD 2.2), and 67.9% of the patients could exercise in the prescribed intensity for at least 3 days per week. Patients' peak VO2 (P = 0.041) and peak metabolic equivalents (P = 0.018) were significantly increased, low-density lipoprotein (P = 0.036) and diastolic blood pressure at rest (P = 0.044) were significantly decreased, and depression (GAD-7, P = 0.014) and anxiety (PHQ-9, P = 0.013) were significantly improved. Conclusions: It is feasible, safe, and helpful for stable CHD patients to use the app for prescribed exercise tutoring with videos combined with wearable devices to monitor heart rate. Trial Registration: ChiCTR1800019144.

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The aim of this study was to examine the goodness of fit and prediction accuracy of general and individual relationships between the maximum number of repetitions completed in a set (XRM) and the fastest repetition in the set (XRM-velocity relationship) in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests, 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min of inter-set rest. A greater goodness of fit was found for individual XRM-velocity relationships (R2 = 0.98; residual standard error [RSE] = 1.01-1.15) compared to general XRM-velocity relationships (R2 = 0.45-0.49; RSE = 3.44-3.66). Individual, but not general XRM-velocity relationships established in the first testing session yielded acceptable prediction accuracy (mean error = 1.96 vs 2.81 repetitions) of XRM in the subsequent testing session. Sex, training status and history, and personality traits did not affect the goodness of fit of general and individual XRM-velocity relationships or their prediction accuracy, suggesting the potential generalisability of those findings among resistance-trained populations. Therefore, individual XRM-velocity relationships can be used to prescribe loads matching an intended XRM by recording only the fastest velocity of the set with a given load and predicting, with reasonable accuracy, the XRM for the individual.

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Traditional exercise training monitoring is based on invasive blood testing methods. As sweat can reveal abundant blood-related physiological information about health, wearable sweat sensors have received significant research attention and become increasingly popular in the field of exercise training monitoring. However, most of these sensors are used to measure physical indicators such as heart rate, blood pressure, respiration, etc., demanding a versatile sensor that can detect relevant biochemical indicators in body fluids. In this work, we proposed a wearable microfluidic sweat chip combined with smartphone image processing to realize non-invasive in situ analysis of epidermal sweat for sports practitioners. The polydimethylsiloxane (PDMS) based chip was modified with nonionic surfactants to ensure good hydrophilicity for the automatic collection of sweat. Besides, a simple, reliable, and low-cost paper-based sensor was prepared for high-performance sensing of glucose concentration and pH in sweat. Under optimized conditions, this proposed chip can detect glucose with low concentrations from 0.05 mM to 0.40 mM, with a pH range of 4.0 to 6.5 for human sweat. The ability of this microfluidic chip for human sweat analysis was demonstrated by dynamically tracking the changes in glucose concentration and pH in long-distance running subjects.

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PURPOSE: The aim of this study was to examine the goodness of fit, prediction accuracy, and stability of general and individual relationships between velocity loss and the percentage of completed repetitions out of maximum possible (VL-%repetitions) in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. METHODS: Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests, 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min inter-set rest. RESULTS: The findings question the utility of using general and individual VL-%repetitions relationships to prescribe training volume with free-weight back squats as (1) the agreement in the %repetitions completed until reaching a given velocity loss threshold across two consecutive testing sessions was unacceptable, regardless of the load used; and (2) the ability of general and individual VL-%repetitions relationships to predict %repetitions in a subsequent testing session were poor (absolute errors > 10%). Sex, training status and history, and personality traits did not affect the goodness of fit of general and individual VL-%repetitions relationships or their prediction accuracy, suggesting potential generalisability of those findings among resistance-trained populations. CONCLUSIONS: VL-%repetitions relationships do not seem to provide any additional benefits compared to costless, traditional methods and hence should not be used for monitoring and prescribing resistance training with a free-weight back squat exercise.

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SLOfit Lifelong is a public health initiative which was created to upgrade a well-established, national physical fitness surveillance system for Slovenian schoolchildren that has been collecting annual fitness and health data for over three decades. The ultimate objective of creating SLOfit Lifelong was to build a modern societal infrastructure with the capacity and ability to detect future causal associations between childhood physical fitness trends and future health outcomes based on the lifelong surveillance of one's own fitness status. By instilling citizens with an ambition to test, understand, and follow-up their own physical fitness and health status (including related health risk factors), this initiative provides the technical support and expert feedback needed to engender greater individual control over understanding (and thus modulating), one's own physical fitness status as they progress into older adulthood. This perspective paper details the extensive approach taken to devise appropriate fitness test batteries for adults and older adults which can also relate to the student version of the original SLOfit test database, including establishing criterion health risk zones and a public approach to establish this national, citizen-driven health feedback framework. Through its sophisticated online web applications, social media, print media, and outreach workshops, SLOfit Lifelong provides the expert support for public health engagement by fostering positive lifelong physical literacy experiences an individual can enjoy across their aging journey.

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For more than a century, many concepts and several theories and principles pertaining to the goals, organization, methodology and evaluation of the effects of resistance training (RT) have been developed and discussed between coaches and scientists. This cumulative body of knowledge and practices has contributed substantially to the evolution of RT methodology. However, a detailed and rigorous examination of the existing literature reveals many inconsistencies that, unless resolved, could seriously hinder further progress in our field. The purpose of this review is to constructively expose, analyze and discuss a set of anomalies present in the current RT methodology, including: (a) the often inappropriate and misleading terminology used, (b) the need to clarify the aims of RT, (c) the very concept of maximal strength, (d) the control and monitoring of the resistance exercise dose, (e) the existing programming models and (f) the evaluation of training effects. A thorough and unbiased examination of these deficiencies could well lead to the adoption of a revised paradigm for RT. This new paradigm must guarantee a precise knowledge of the loads being applied, the effort they involve and their effects. To the best of our knowledge, currently this can only be achieved by monitoring repetition velocity during training. The main contribution of a velocity-based RT approach is that it provides the necessary information to know the actual training loads that induce a specific effect in each athlete. The correct adoption of this revised paradigm will provide coaches and strength and conditioning professionals with accurate and objective information concerning the applied load (relative load, level of effort and training effect). This knowledge is essential to make rational and informed decisions and to improve the training methodology itself.

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Background: Small-sided games (SSGs) are drill-based and constrained exercises designed to promote a technical/tactical and physiological/physical stimulus on players while preserving some dynamics of the real game. However, as a dynamic game, they can offer some variability making the prediction of the stimulus hardest for the coach. Aim: The purpose of this study was to analyze the between-session and within-player variability of heart rates and locomotor responses of young male soccer players in 3v3 and 5v5 small-sided game formats. Methods: This study followed a repeated-measures study design. Twenty soccer players were enrolled in a study design in which the SSG formats 3v3 and 5v5 were performed consecutively across four days. Twenty under-17 male youth soccer players (16.8 ± 0.4 years old) voluntarily participated in this study. Participants were monitored using a Polar Team Pro for measuring the heart rate mean and maximum, distances covered at different speed thresholds, and peak speed. Results: Between-players variability revealed that maximum heart rate was the outcome with a smaller coefficient of variation (3v3 format: 3.1% to 11.1%; 5v5 format: 6.6% to 15.2%), while the distance covered at Z5 (3v3 format: 82.5% to 289.8%; 5v5 format: 94.0% to 221.1%). The repeated measures ANOVA revealed that the four games tested were different in the within-player variability considering the maximum heart rate (p = 0.032), total distance (p < 0.001), and distances at zone 1, 2, and 5 of speed (p < 0.001). Conclusions: The smaller small-sided game tested promotes greater within-player variability in locomotor demands while promoting smaller within-player variability heart rate responses. Possibly, 5v5 is more recommended to stabilize the locomotor demands, while the 3v3 is recommended to stabilize the heart rate stimulus.

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BACKGROUND: Insightful feedback generation for daily home-based stroke rehabilitation is currently unavailable due to the inefficiency of exercise inspection done by therapists. We aim to produce a compact anomaly representation that allows a therapist to pay attention to only a few specific sections in a long exercise session record and boost their efficiency in feedback generation. METHODS: This study proposes a data-driven technique to model a repetitive exercise using unsupervised phase learning on an artificial neural network and statistical learning on principal component analysis (PCA). After a model is built on a set of normal healthy movements, the model can be used to extract a sequence of anomaly scores from a movement of the same prescription. RESULTS: The method not only works on a standard marker-based motion capture system but also performs well on a more compact and affordable motion capture system based-on Kinect V2 and wrist-worn inertial measurement units that can be used at home. An evaluation of four different exercises shows its potential in separating anomalous movements from normal ones with an average area under the curve (AUC) of 0.9872 even on the compact motion capture system. CONCLUSIONS: The proposed processing technique has the potential to help clinicians in providing high-quality feedback for telerehabilitation in a more scalable way.

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Strengthening muscles can reduce body fat, increase lean muscle mass, maintain independence while aging, manage chronic conditions, and improve balance, reducing the risk of falling. The most critical factor inducing effectiveness in strength training is neuromuscular connection by adopting attentional focus during training. However, this is troublesome for end users since numerous fitness tracking devices or applications do not provide the ability to track the effectiveness of users' workout at the neuromuscular level. A practical approach for detecting attentional focus by assessing neuromuscular activity through biosignals has not been adequately evaluated. The challenging task to make the idea work in a real-world scenario is to minimize the cost and size of the clinical device and use a recognition system for muscle contraction to ensure a good user experience. We then introduce a multitasking and multiclassification network and an EMG shirt attached with noninvasive sensing electrodes that firmly fit to the body's surface, measuring neuron muscle activity during exercise. Our study exposes subjects to standard free-weight exercises focusing on isolated and compound muscle on the upper limb. The results of the experiment show a 94.79% average precision at different maximum forces of attentional focus conditions. Furthermore, the proposed system can perform at different lifting weights of 67% and 85% of a person's 1RM to recognize individual exercise effectiveness at the muscular level, proving that adopting attentional focus with low-intensity exercise can activate more upper-limb muscle contraction.

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(1) Background: Current vestibular rehabilitation therapy is an exercise-based approach aimed at promoting gaze stability, habituating symptoms, and improving balance and walking in patients with mild traumatic brain injury (mTBI). A major component of these exercises is the adaptation of the vestibulo-ocular reflex (VOR) and habituation training. Due to acute injury, the gain of the VOR is usually reduced, resulting in eye movement velocity that is less than head movement velocity. There is a higher chance for the success of the therapy program if the patient (a) understands the exercise procedure, (b) performs the exercises according to the prescribed regimen, (c) reports pre- and post-exercise symptoms and perceived difficulty, and (d) gets feedback on performance. (2) Methods: The development and laboratory evaluation of VestAid, an innovative, low-cost, tablet-based system that helps patients perform vestibulo-ocular reflex (VORx1) exercises correctly at home without therapist guidance, is presented. VestAid uses the tablet camera to automatically assess patient performance and compliance with exercise parameters. The system provides physical therapists (PTs) with near real-time, objective (head speed and gaze fixation compliance), and subjective (perceived difficulty and pre- and post- exercise symptoms) metrics through a web-based provider portal. The accuracy of the head-angle and eye-gaze compliance metrics was evaluated. The accuracy of estimated head angles calculated via VestAid's low-complexity algorithms was compared to the state-of-the-art deep-learning method on a public dataset. The accuracy of VestAid's metric evaluation during the VORx1 exercises was assessed in comparison to the output of an inertial measurement unit (IMU)-based system. (3) Results: There are low mean interpeak time errors (consistently below 0.1 s) across all speeds of the VORx1 exercise, as well as consistently matching numbers of identified peaks. The spatial comparison (after adjusting for the lag measured with the cross-correlation) between the VestAid and IMU-based systems also shows good matching, as shown by the low mean absolute head angle error, in which for all speeds, the mean is less than 10 degrees. (4) Conclusions: The accuracy of the system is sufficient to provide therapists with a good assessment of patient performance. While the VestAid system's head pose evaluation model may not be perfectly accurate as a result of the occluded facial features when the head moves further towards an extreme in pitch and yaw, the head speed measurements and associated compliance measures are sufficiently accurate for monitoring patients' VORx1 exercise compliance and general performance.

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BACKGROUND: Exercise has been recommended as a cornerstone for diabetes management. Supervised exercise is more efficient than unsupervised exercise but is less convenient and accessible. OBJECTIVE: We aimed to determine the efficiency of exercise using a fitness app and heart rate band to remotely monitor patients with type 2 diabetes in comparison with that of traditional exercise. METHODS: Patients with type 2 diabetes without severe complications or comorbidities were recruited to participate in this multicenter randomized controlled trial and were allocated to either the intervention or control group (1:1 ratio). Participants in both groups were asked to engage in moderate to vigorous physical activity for at least 150 minutes per week; each participant was prescribed individualized exercises. Participants in the intervention group were asked to follow exercise videos on the app and to wear a chest band; heart rate, exercise duration, and exercise intensity were recorded by the app. Participants in the control group self-reported exercise intensity and duration. Cardiopulmonary endurance, body composition, blood glucose level, and insulin level were assessed before and after a 3-month exercise program. RESULTS: Of the 101 participants who were enrolled, the majority of them (85/101, 84.2%) completed the study. Both groups had similar baseline characteristics, with the exception that participants in the intervention group were slightly younger and less likely to have hypertension. Self-reported exercise duration was longer than app-recorded exercise duration (control: mean 214 minutes/week; intervention: mean 193 minutes/week); in addition, a higher proportion of participants in the control group (29/41, 71%) than in the intervention group (18/44, 41%) met the 150-minute target for moderate to vigorous physical activity. However, compared with the control group, the intervention group had a larger increase in cardiopulmonary endurance (mean difference -2.0 bpm [beats per minute] vs 1.0 bpm; P=.02) and a larger decrease in body fat percentage (mean difference -1.8% vs -0.8%; P=.01). There was no difference in hemoglobin A1c level reduction between the two groups, yet more participants in the intervention group stopped taking their antidiabetic drugs or had their dosages lowered by an endocrinologist, compared with those in the control group. There were no serious adverse events in either group. CONCLUSIONS: This was the first randomized controlled trial in China, to our knowledge, to test the efficiency of exercise using a fitness app and heart rate band to remotely monitor prescribed exercise in patients with type 2 diabetes. The findings of our study suggest that exercise programs may be more efficient if participants are remotely monitored with an app and heart rate band than if participants are not monitored. TRIAL REGISTRATION: Chinese Clinical Trial Register ChiCTR1800015963; http://www.chictr.org.cn/showprojen.aspx?proj=27080.

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Current Continuous Glucose Monitors (CGM) exhibit increased estimation error during periods of aerobic physical activity. The use of readily-available exercise monitoring devices opens new possibilities for accuracy enhancement during these periods. The viability of an array of physical activity signals provided by three different wearable devices was considered. Linear regression models were used in this work to evaluate the correction capabilities of each of the wearable signals and propose a model for CGM correction during exercise. A simple two-input model can reduce CGM error during physical activity (17.46% vs. 13.8%, p < 0.005) to the magnitude of the baseline error level (13.61%). The CGM error is not worsened in periods without physical activity. The signals identified as optimal inputs for the model are "Mets" (Metabolic Equivalent of Tasks) from the Fitbit Charge HR device, which is a normalized measurement of energy expenditure, and the skin temperature reading provided by the Microsoft Band 2 device. A simpler one-input model using only "Mets" is also viable for a more immediate implementation of this correction into market devices.

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High intensity interval training (HIIT) is now recognized in international clinical-based exercise guidelines as an appropriate and beneficial adjunct to moderate intensity continuous training. HIIT involves alternating periods of high intensity aerobic exercise with light recovery exercise or no exercise, allowing for greater physiological stimulus and adaptation than moderate intensity continuous training (MICT) for cardiorespiratory fitness and other cardiometabolic processes. However, there is no universal criteria or framework for the prescription and monitoring of HIIT in clinical populations, and safety concerns remain a common barrier for implementing HIIT as standard care. Historically, exercise intensity has been prescribed using heart rate (HR) targets derived from either a predicted maximal HR (HRmax) or from an attempt to objectively measure HRmax. However, using this approach alone has a number of limitations. Here we provide guidelines to improve the delivery of HIIT in cardiometabolic populations using 1) a framework for HIIT prescription using a combination of objective and subjective measures of exercise intensity, and 2) clinical considerations for assessment and monitoring to maximize patient safety. The framework involves an individualized step-by-step process to calculate, validate, and calibrate HR target zones for HIIT training to allow for appropriate workload prescription and progression. We strongly recommend this framework be used in future clinical trials investigating HIIT.

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Facebook, with a record 1.7+ billion monthly active users, is increasingly the platform of choice for a multitude of e-health applications. This work presents our experience in exercise monitoring using a custom-built Facebook application for activity self-reporting. A group of young adults (n = 49, age = 24 ± 7 years, body mass index (BMI) = 22.5 ± 3) took part in a 5-week pilot study, part of the NutriHeAl intervention project. Participants reported their daily exercise activities for an average of 33 ± 5 days and were also equipped with digital pedometers (Fibit Zips) for the full duration, allowing the evaluation of their activity reporting accuracy by comparing steps/min to a 'truth ceiling' value for two pre-defined exercise categories (2 + and 3+ metabolic equivalent of task (MET) intensity). We found that users not only reported their exercise consistently for an extended period of time but also achieved an average accuracy score of 71 ± 21% (82 ± 18% for 2+ MET exercises), making this novel exercise monitoring methodology a formidable tool for a modern physician's digital arsenal. In addition, the developed tools and processes can also be re-used in other e-health applications.

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The advancement of perioperative medicine is leading to greater diversity in development of pre-surgical interventions, implemented to reduce patient surgical risk and enhance post-surgical recovery. Of these interventions, the prescription of pre-operative exercise training is gathering momentum as a realistic means for enhancing patient surgical outcome. Indeed, the general benefits of exercise training have the potential to pre-operatively optimise several pre-surgical risks factors, including cardiorespiratory function, frailty and cognitive function. Any exercise programme incorporated into the pre-operative pathway of care needs to be effective and time efficient in that any fitness gains are achievable in the limited period between the decision for surgery and operation (e.g. 4 weeks). Fortunately, there is a large volume of research describing effective and time-efficient exercise training programmes within the discipline of sports science. Accordingly, the objective of our commentary is to synthesise contemporary exercise training research, both from non-clinical and clinical populations, with the overarching aim of informing the development of effective and time-efficient pre-surgical exercise training programmes. The development of such exercise training programmes requires the careful consideration of several key principles, namely frequency, intensity, time, type and progression of exercise. Therefore, in light of more recent evidence demonstrating the effectiveness and time efficiency of high-intensity interval training-which involves brief bouts of intense exercise interspersed with longer recovery periods-the principles of exercise training programme design will be discussed mainly in the context of such high-intensity interval training programmes. Other issues pertinent to the development, implementation and evaluation of pre-operative exercise training programmes, such as individual exercise prescription, training session monitoring and potential barriers and risks to high-intensity exercise are also discussed. The evidence presented suggests that individually prescribed and supervised high-intensity interval training programmes, encompassing a variety of exercise modes represent an effective and safe means of exercise therapy prior to surgery.