Incorporating Internal and External Training Load Measurements in Clinical Decision Making After ACL Reconstruction: A Clinical Commentary

# Background and Purpose Poor outcomes after anterior cruciate ligament reconstruction (ACLr), including the relatively high risk of suffering a subsequent ACL injury, suggest the need to optimize rehabilitation and return-to-sport testing. The purpose of this commentary is to introduce clinicians to the concept of monitoring training load during rehabilitation, to review methods of quantifying internal and external loads, and to suggest ways that these technologies can be incorporated into rehabilitation progressions and return-to-sport decisions after anterior ACLr. # Description of Topic with Related Evidence Quantifying and identifying the effects of training load variables, external (distance, impacts, decelerations) and internal (heart rate, heart rate variability) workload, during rehabilitation can indicate both positive (improved physical, physiological, or psychological capacity) or negative (heightened risk for injury or illness) adaptations and allow for the ideal progression of exercise prescription. When used during return-to-sport testing, wearable technology can provide robust measures of movement quality, readiness, and asymmetry not identified during performance-based testing. # Discussion / Relation to Clinical Practice Researchers have reported the actual in-game demands of men and women of various ages and competition levels during multi-directional sport. Wearable technology can provide similar variables during rehabilitation, home exercise programs, and during on-field transition back to sport to ensure patients have met the expected fitness capacity of their sport. Additionally, clinicians can use internal load measures to objectively monitor patient’s physiological responses to rehabilitation progressions and recovery rather than relying on subjective patient-reported data. # Level of Evidence

Robust Estimation of Physical Activity by Adaptively Fusing Multiple Parameters

Hörmann T, Christ P, Hesse M, Rückert U. Robust Estimation of Physical Activity by Adaptively Fusing Multiple Parameters. In: Wearable and Implantable Body Sensor Networks (BSN), 2015 IEEE 12th International Conference on. IEEE; 2015: 1-6

A Software Assistant for User-Centric Calibration of a Wireless Body Sensor

Hörmann T, Hesse M, Adams M, Rückert U. A Software Assistant for User-Centric Calibration of a Wireless Body Sensor. In: 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE; 2016: 183-188.Body sensors have a promising contribution to health promotion in many areas of daily life (telemedicine, corporate health care or recreational sports). However, the valid measurement of vital signs and kinematic data strongly depends on the signals' quality and the users' compliance (proper usage). Although, there is a lot of research work concerning accuracy and calibration of wireless body sensors the human user is typically not involved. Thus, in this work, we present a software assistant (wizard) that guides users during the process of attaching and setting up a wireless body sensor. Furthermore, insights of the implemented software as well as the utilized quality measures and calibration steps are given (ECG, respiration sensor and accelerometer). With the proposed software assistant, the users are instructed to correctly attach the body sensor and calibrate or verify the operability of the various sensor elements. The primary goal is to encourage compliance and the users' sense of control. In this way, we want to reduce faulty operation and ensure optimal signal quality

Exercise Prescription in Cardiac Rehabilitation

This book has been reviewed by two (or more) external single-blind reviewers. The opinions expressed in the book do not reflect the view of the publisher. ...read more Keywords: cardiac rehabilitation, exercise prescription, interval trainin

Exercise Prescription in Cardiac Rehabilitation

The use of ingredients obtained from waste is becoming a necessity to reduce worldwide pollution, saving both environment and earth biodiversity. In fact, according to Fritjof Capra “The survival of humanity will depend from our ecological knowledge, the capacity of understanding the fundamentals of ecology and to live accordingly with them”. Please see the complete preface attached

Exercise Prescription in Cardiac Rehabilitation

This book has been reviewed by two (or more) external single-blind reviewers. The opinions expressed in the book do not reflect the view of the publisher. ...read more Keywords: cardiac rehabilitation, exercise prescription, interval trainin

Cardiorespiratory, kinematic, neuromuscular and metabolic characteristics during the recovery period after an ultramarathon race

Includes abstract.Includes bibliographical references (p. 325-399).The aim of this study was to investigate the effects of exercise-induced muscle damage caused by a 90 km ultramarathon on submaximal oxygen consumption and stride length. The experimental group consisted of 11 male runners (39.7 ± 9.3 years) competing in a 90 km ultramarathon. Ten male runners (41.0 ± 10.8 years) who did not run the 90 km ultramarathon formed the control group. Maximum oxygen consumption and peak treadmill running speed were measured two weeks before the ultramarathon. Daily measurements of muscle pain and plasma creatine kinase (CK) activity were recorded for seven days after the ultramarathon. Muscle pain, plasma CK activity, and blood lactate concentrations were recorded before, and oxygen consumption, respiratory exchange ratio (RER), heart rate, rate of perceived exertion (RPE), and stride length were all measured during a 15-minute submaximal treadmill test seven days before the ultramarathon, and on days 4, 7, 14, 21, and 28 after the ultramarathon. Peak blood lactate concentrations were determined 3 minutes after the completion of each treadmill test. Plasma CK activity and muscle pain remained significantly elevated in the experimental group for two days (p < 0.00002) and four days (p < 0.02) respectively after the ultramarathon. There was a significant increase in the post-submaximal treadmill test blood lactate concentrations, compared to pre-test values for each day (p < 0.00001). Submaximal oxygen consumption was significantly reduced in the experimental group for up to 28 days (p < 0.0004), and stride length was significantly reduced for 14 days (p < 0.05) after the ultramarathon. Furthermore, in the experimental group RER was significantly increased for up to seven days (p < 0.05), and RPE was significantly increased for up to four days (p < 0.04) after the ultramarathon. In conclusion, the decreased submaximal oxygen consumption following the ultramarathon may be interpreted as a positive training adaptation. However, other responses to the ultramarathon were not compatible with improved running performance. Furthermore, symptoms other than pain should be used to define the recovery period after an ultramarathon race

The Athlete’s Heart and Machine Learning: A Review of Current Implementations and Gaps for Future Research

Background: Intense training exercise regimes cause physiological changes within the heart to help cope with the increased stress, known as the “athlete’s heart”. These changes can mask pathological changes, making them harder to diagnose and increasing the risk of an adverse cardiac outcome. Aim: This paper reviews which machine learning techniques (ML) are being used within athlete’s heart research and how they are being implemented, as well as assesses the uptake of these techniques within this area of research. Methods: Searches were carried out on the Scopus and PubMed online datasets and a scoping review was conducted on the studies which were identified. Results: Twenty-eight studies were included within the review, with ML being directly referenced within 16 (57%). A total of 12 different techniques were used, with the most popular being artificial neural networks and the most common implementation being to perform classification tasks. The review also highlighted the subgroups of interest: predictive modelling, reviews, and wearables, with most of the studies being attributed to the predictive modelling subgroup. The most common type of data used was the electrocardiogram (ECG), with echocardiograms being used the second most often. Conclusion: The results show that over the last 11 years, there has been a growing desire of leveraging ML techniques to help further the understanding of the athlete’s heart, whether it be by expanding the knowledge of the physiological changes or by improving the accuracies of models to help improve the treatments and disease management

Muscle activation patterns in shoulder impingement patients

Introduction: Shoulder impingement is one of the most common presentations of shoulder joint problems 1. It appears to be caused by a reduction in the sub-acromial space as the humerus abducts between 60o -120o – the 'painful arc'. Structures between the humeral head and the acromion are thus pinched causing pain and further pathology 2. Shoulder muscle activity can influence this joint space but it is unclear whether this is a cause or effect in impingement patients. This study aimed to observe muscle activation patterns in normal and impingement shoulder patients and determine if there were any significant differences. Method: 19 adult subjects were asked to perform shoulder abduction in their symptomatic arm and non-symptomatic. 10 of these subjects (age 47.9 ± 11.2) were screened for shoulder impingement, and 9 subjects (age 38.9 ± 14.3) had no history of shoulder pathology. Surface EMG was used to collect data for 6 shoulder muscles (Upper, middle and lower trapezius, serratus anterior, infraspinatus, middle deltoids) which was then filtered and fully rectified. Subjects performed 3 smooth unilateral abduction movements at a cadence of 16 beats of a metronome set at 60bpm, and the mean of their results was recorded. T-tests were used to indicate any statistical significance in the data sets. Significance was set at P<0.05. Results: There was a significant difference in muscle activation with serratus anterior in particular showing a very low level of activation throughout the range when compared to normal shoulder activation patterns (<30%). Middle deltoid recruitment was significantly reduced between 60-90o in the impingement group (30:58%).Trends were noted in other muscles with upper trapezius and infraspinatus activating more rapidly and erratically (63:25%; 60:27% respectively), and lower trapezius with less recruitment (13:30%) in the patient group, although these did not quite reach significance. Conclusion: There appears to be some interesting alterations in muscle recruitment patterns in impingement shoulder patients when compared against their own unaffected shoulders and the control group. In particular changes in scapula control (serratus anterior and trapezius) and lateral rotation (infraspinatus), which have direct influence on the sub-acromial space, should be noted. It is still not clear whether these alterations are causative or reactionary, but this finding gives a clear indication to the importance of addressing muscle reeducation as part of a rehabilitation programme in shoulder impingement patients

Brazilian Cardiovascular Rehabilitation Guideline – 2020

Resumo não disponíve