Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden.
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ABSTRACT:
SUBMITTER: Seshadri DR
PROVIDER: S-EPMC7859639 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden.
Seshadri Dhruv R DR Thom Mitchell L ML Harlow Ethan R ER Gabbett Tim J TJ Geletka Benjamin J BJ Hsu Jeffrey J JJ Drummond Colin K CK Phelan Dermot M DM Voos James E JE
Frontiers in sports and active living 20210121
Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and ...[more]
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Project description:BACKGROUND:The relationship of training load to injury using wearable technology has not been investigated in professional American football players. The primary objective of this study was to determine the correlation between player workload and soft tissue injury over the course of a football season utilizing wearable global positioning system (GPS) technology. HYPOTHESIS:Increased training load is associated with a higher incidence of soft tissue injuries. STUDY DESIGN:Case-control study. LEVEL OF EVIDENCE:Level 3. METHODS:Player workloads were assessed during preseason and regular-season practice sessions using GPS tracking and triaxial accelerometry from 2014 to 2016. Soft tissue injuries were recorded during each season. Player workload during the week of injury (acute) and average weekly workload during the 4 weeks (chronic) prior to injury were determined for each injury and in uninjured position-matched controls during the same week. A matched-pairs t test was used to determine differences in player workload. Subgroup analysis was also conducted to determine whether observed effects were confounded by training period and type of injury. RESULTS:In total, 136 lower extremity injuries were recorded. Of the recorded injuries, 101 injuries with complete GPS and clinical data were included in the analysis. Injuries were associated with greater increases in workload during the week of injury over the prior month when compared with uninjured controls. Injured players saw a 111% (95% CI, 66%-156%) increase in workload whereas uninjured players saw a 73% (95% CI, 34%-112%) increase in workload during the week of injury (P = 0.032). Individuals who had an acute to chronic workload ratio higher than 1.6 were 1.5 times more likely to sustain an injury relative to time- and position-matched controls (64.6% vs 43.1%; P = 0.004). CONCLUSION:Soft tissue injuries in professional football players were associated with sudden increases in training load over the course of a month. This effect seems to be especially pronounced during the preseason when player workloads are generally higher. These results suggest that a gradual increase of training intensity is a potential method to reduce the risk of soft tissue injury. CLINICAL RELEVANCE:Preseason versus regular-season specific training programs monitored with wearable technology may assist team athletic training and medical staff in developing programs to optimize player performance.
| S-EPMC6931176 | biostudies-literature
Project description:Background: Current sports medicine and rehabilitation trends indicate an increasing use of wearable technology. The ability of these devices to collect, transmit, and process physiological, biomechanical, bioenergy, and environmental data may aid in anterior cruciate ligament reconstruction (ACLR) workload monitoring and return-to-sport decision-making. In addition, their ease of use allows assessments to occur outside the clinical or laboratory settings and across a broader timeline. Purpose: To (1) determine how wearable technology can assess external workload deficits between limbs (involved and uninvolved) and between groups (healthy controls vs patients with ACLR) during physical activity (PA) or sport and (2) describe the types of sensors, sensor specifications, assessment protocols, outcomes of interest, and participant characteristics from the included studies. Study Design: Scoping review; Level of evidence, 4. Methods: In February 2023, a systematic search was performed in the MEDLINE, EMBASE, CINAHL, SPORTDiscus, Scopus, IEEE Xplore, Compendex, and ProQuest Dissertations and Theses Global databases. Eligible studies included assessments of PA or sports workloads via wearable technology after ACLR. Results: Twenty articles met eligibility criteria and were included. The primary activity assessed was activities of daily living, although rehabilitation, training, and competition were also represented. Accelerometers, global positioning system units, pedometers, and pressure sensor insoles were worn to collect external workload data, which was quantified as kinetic, kinematic, and temporospatial data. Daily steps (count) and moderate to vigorous PA (min/day or week) were the most common units of measurement. A limited number of studies included outcomes related to between-limb asymmetries. Conclusion: The findings of this scoping review highlight the versatility of wearable technologies to collect patients’ kinetic, kinematic, and temporospatial data and assess external workload outcomes after ACLR. In addition, some wearable technologies identified deficits in workload compared with healthy controls and between reconstructed and unaffected limbs.
| S-EPMC10467401 | biostudies-literature
Project description:BackgroundPhysical exercise is associated with decreased cardiovascular disease (CVD) risk, but recent large-scale trials suggest that exercise alone is insufficient to reduce CVD events in high-risk older adults.PurposeThis pilot randomized clinical trial aimed to collect critical data on feasibility, safety, and protocol integrity necessary to design a fully powered randomized controlled trial (RCT) and evaluate the impact of combining structured exercise with an intervention designed to enhance non-exercise physical activity (EX+NEPA) compared to EX alone.MethodsForty participants aged ≥60 years with moderate-to-high risk of coronary heart disease events were randomly assigned to either the EX+NEPA or EX groups and followed for 20 weeks. Both groups underwent a twice-weekly, 8-week center-based exercise intervention with aerobic and resistance exercises. EX+NEPA group also received a wearable activity tracking device along with behavioral monitoring and feedback throughout the study. Study outcomes were evaluated at 8 and 20 weeks.ResultsData are presented as adjusted mean change of the differences over time with 95% confidence intervals at 20 weeks. Relative to EX, the change in steps/day at 20 weeks was 1994 (-40.27, 4028) higher for EX+NEPA. For sedentary time at close-out, the EX+NEPA group was -6.8 (-45.2, 31.6) min/day relative to EX. The between-group differences for systolic and diastolic blood pressure were -9.9 (-19.6, -0.3) and -1.8 (-6.9, 3.3) mmHg, respectively.ConclusionThe addition of wearable technology intervention appeared to positively influence daily activity patterns and changes in blood pressure - potentially improving risk factors for CVD. A fully powered randomized trial is needed to ultimately test this hypothesis.
| S-EPMC6815758 | biostudies-literature
Project description:BackgroundHigh levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. The aim of this paper is to evaluate the effectiveness of such technology enhanced interventions aimed at reducing SB in healthy adults and to examine the behaviour change techniques (BCTs) used.MethodsFive electronic databases were searched to identify randomised-controlled trials (RCTs), published up to June 2016. Interventions using computer, mobile or wearable technologies to facilitate a reduction in SB, using a measure of sedentary time as an outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Collaboration's tool and interventions were coded using the BCT Taxonomy (v1).ResultsMeta-analysis of 15/17 RCTs suggested that computer, mobile and wearable technology tools resulted in a mean reduction of -41.28 min per day (min/day) of sitting time (95% CI -60.99, -21.58, I2 = 77%, n = 1402), in favour of the intervention group at end point follow-up. The pooled effects showed mean reductions at short (≤ 3 months), medium (>3 to 6 months), and long-term follow-up (>6 months) of -42.42 min/day, -37.23 min/day and -1.65 min/day, respectively. Overall, 16/17 studies were deemed as having a high or unclear risk of bias, and 1/17 was judged to be at a low risk of bias. A total of 46 BCTs (14 unique) were coded for the computer, mobile and wearable components of the interventions. The most frequently coded were "prompts and cues", "self-monitoring of behaviour", "social support (unspecified)" and "goal setting (behaviour)".ConclusionInterventions using computer, mobile and wearable technologies can be effective in reducing SB. Effectiveness appeared most prominent in the short-term and lessened over time. A range of BCTs have been implemented in these interventions. Future studies need to improve reporting of BCTs within interventions and address the methodological flaws identified within the review through the use of more rigorously controlled study designs with longer-term follow-ups, objective measures of SB and the incorporation of strategies to reduce attrition.Trial registrationThe review protocol was registered with PROSPERO: CRD42016038187.
| S-EPMC5553917 | biostudies-literature
Project description:Persons aged over 65 years account for over the vast majority of healthcare expenditures and deaths attributable to cardiovascular disease (CVD). Accordingly, reducing CVD risk among older adults is an important public health priority. Structured physical activity (i.e. exercise) is a well-documented method of decreasing CVD risk, but recent large-scale trials suggest that exercise alone is insufficient to reduce CVD events in high-risk populations of older adults. Thus adjuvant strategies appear necessary to reduce CVD risk. Accumulating evidence indicates that prolonged sedentary behavior (e.g. sitting) has detrimental health effects that are independent of engagement in recommended levels of moderate-intensity exercise. Yet clinical trials in this area are lacking. We hypothesize that exercise, when combined with a novel technology based intervention specifically designed to reduce sedentary behavior will reduce CVD risk among sedentary older adults. The purpose of this study is to evaluate the feasibility and efficacy of combining a traditional, structured exercise intervention with an innovative intervention designed to decrease sedentary behavior and increase non-exercise physical activity (NEPA). This study will provide us with critical data necessary to design and implement a full-scale trial to test our central hypothesis. Participants aged ≥60 years with moderate to high risk of coronary heart disease (CHD) events are randomly assigned to either the exercise and technology intervention (EX+NEPA) or exercise alone (EX) groups. Study dependent outcomes include changes in 1) daily activity patterns, 2) blood pressure, 3) exercise capacity, 4) waist circumference, and 5) circulating indices of cardiovascular function. This study will provide critical information for designing a fully-powered clinical trial, which could have health implications for the ever increasing population of older adults.
| S-EPMC5608105 | biostudies-literature
Project description:BackgroundTo experience external objects in such a way that they are perceived as an integral part of one's own body is called embodiment. Wearable technology is a category of objects, which, due to its intrinsic properties (eg, close to the body, inviting frequent interaction, and access to personal information), is likely to be embodied. This phenomenon, which is referred to in this paper as wearable technology embodiment, has led to extensive conceptual considerations in various research fields. These considerations and further possibilities with regard to quantifying wearable technology embodiment are of particular value to the mobile health (mHealth) field. For example, the ability to predict the effectiveness of mHealth interventions and knowing the extent to which people embody the technology might be crucial for improving mHealth adherence. To facilitate examining wearable technology embodiment, we developed a measurement scale for this construct.ObjectiveThis study aimed to conceptualize wearable technology embodiment, create an instrument to measure it, and test the predictive validity of the scale using well-known constructs related to technology adoption. The introduced instrument has 3 dimensions and includes 9 measurement items. The items are distributed evenly between the 3 dimensions, which include body extension, cognitive extension, and self-extension.MethodsData were collected through a vignette-based survey (n=182). Each respondent was given 3 different vignettes, describing a hypothetical situation using a different type of wearable technology (a smart phone, a smart wristband, or a smart watch) with the purpose of tracking daily activities. Scale dimensions and item reliability were tested for their validity and Goodness of Fit Index (GFI).ResultsConvergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings (>0.70), average variance extracted values (>0.50), and minimum item to total correlations (>0.40) exceeded established threshold values. The reliability of the dimensions was also confirmed as Cronbach alpha and composite reliability exceeded 0.70. GFI testing confirmed that the 3 dimensions function as intercorrelated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (ie, trust, perceived usefulness, involvement, attitude, and continuous intention).ConclusionsThe wearable technology embodiment measurement instrument has shown promise as a tool to measure the extension of an individual's body, cognition, and self, as well as predict certain aspects of technology adoption. This 3-dimensional instrument can be applied to mixed method research and used by wearable technology developers to improve future versions through such things as fit, improved accuracy of biofeedback data, and customizable features or fashion to connect to the users' personal identity. Further research is recommended to apply this measurement instrument to multiple scenarios and technologies, and more diverse user groups.
| S-EPMC6709898 | biostudies-literature
Project description:The unpredictability of epileptic seizures exposes people with epilepsy to potential physical harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure forecasters would reduce the uncertainty associated with seizures but need to be feasible and accessible in the long-term. Wearable devices are perfect candidates to develop non-invasive, accessible forecasts but are yet to be investigated in long-term studies. We hypothesized that machine learning models could utilize heart rate as a biomarker for well-established cycles of seizures and epileptic activity, in addition to other wearable signals, to forecast high and low risk seizure periods. This feasibility study tracked participants' (n = 11) heart rates, sleep, and step counts using wearable smartwatches and seizure occurrence using smartphone seizure diaries for at least 6 months (mean = 14.6 months, SD = 3.8 months). Eligible participants had a diagnosis of refractory epilepsy and reported at least 20 seizures (mean = 135, SD = 123) during the recording period. An ensembled machine learning and neural network model estimated seizure risk either daily or hourly, with retraining occurring on a weekly basis as additional data was collected. Performance was evaluated retrospectively against a rate-matched random forecast using the area under the receiver operating curve. A pseudo-prospective evaluation was also conducted on a held-out dataset. Of the 11 participants, seizures were predicted above chance in all (100%) participants using an hourly forecast and in ten (91%) participants using a daily forecast. The average time spent in high risk (prediction time) before a seizure occurred was 37 min in the hourly forecast and 3 days in the daily forecast. Cyclic features added the most predictive value to the forecasts, particularly circadian and multiday heart rate cycles. Wearable devices can be used to produce patient-specific seizure forecasts, particularly when biomarkers of seizure and epileptic activity cycles are utilized.
| S-EPMC8320020 | biostudies-literature
Project description:BackgroundResource-limited communities in Washington, D.C. have high rates of obesity-related cardiovascular disease in addition to inadequate physical activity (PA) facilities and limited Internet access. Engaging community members in the design and implementation of studies to address these health disparities is essential to the success of community-based PA interventions.ObjectiveThe objective of the study was to use qualitative and quantitative methods to evaluate the feasibility and acceptability of PA-monitoring wristbands and Web-based technology by predominantly African American, church-based populations in resource-limited Washington, D.C. neighborhoods.MethodsTo address cardiovascular health in at-risk populations in Washington, D.C., we joined community leaders to establish a community advisory board, the D.C. Cardiovascular Health and Obesity Collaborative (D.C. CHOC). As their first initiative, the Washington, D.C. Cardiovascular Health and Needs Assessment intends to evaluate cardiovascular health, social determinants of health, and PA-monitoring technologies. At the recommendation of D.C. CHOC members, we conducted a focus group and piloted the proposed PA-monitoring system with community members representing churches that would be targeted by the Cardiovascular Health and Needs Assessment. Participants (n=8) agreed to wear a PA-monitoring wristband for two weeks and to log cardiovascular health factors on a secure Internet account. Wristbands collected accelerometer-based data that participants uploaded to a wireless hub at their church. Participants agreed to return after two weeks to participate in a moderated focus group to share experiences using this technology. Feasibility was measured by Internet account usage, wristband utilization, and objective PA data. Acceptability was evaluated through thematic analysis of verbatim focus group transcripts.ResultsStudy participants (5 males, 3 females) were African American and age 28-70 years. Participant wristbands recorded data on 10.1±1.6 days. Two participants logged cardiovascular health factors on the website. Focus group transcripts revealed that participants felt positively about incorporating the device into their church-based populations, given improvements were made to device training, hub accessibility, and device feedback.ConclusionsPA-monitoring wristbands for objectively measuring PA appear to be a feasible and acceptable technology in Washington, D.C., resource-limited communities. User preferences include immediate device feedback, hands-on device training, explicit instructions, improved central hub accessibility, and designation of a church member as a trained point-of-contact. When implementing technology-based interventions in resource-limited communities, engaging the targeted community may aid in early identification of issues, suggestions, and preferences.ClinicaltrialTrial registrationClinicalTrials.gov NCT01927783; https://clinicaltrials.gov/ct2/show/NCT01927783 (Archived by WebCite at http://www.webcitation.org/6f8wL117u).
| S-EPMC4861844 | biostudies-literature
Project description:BackgroundCurrent technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology.ObjectiveIn one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern.MethodsWe adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray's work was combined with an inductive approach in which new themes were discovered.ResultsOverall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of "whom" to believe, the machine or one's self.ConclusionsThere are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally "dumb" body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.
| S-EPMC7671844 | biostudies-literature
Project description:Skin-compatible printed stretchable conductors that combine a low gauge factor with a high durability over many strain cycles are still a great challenge. Here, a graphene nanoplatelet-based colloidal ink utilizing a skin-compatible thermoplastic polyurethane (TPU) binder with adjustable rheology is developed. Stretchable conductors that remain conductive even under 100% strain and demonstrate high fatigue resistance to cyclic strains of 20-50% are realized via printing on TPU. The sheet resistances of these conductors after drying at 120 °C are as low as 34 Ω □-1 mil-1. Furthermore, photonic annealing at several energy levels is used to decrease the sheet resistance to <10 Ω □-1 mil-1, with stretchability and fatigue resistance being preserved and tunable. The high conductivity, stretchability, and cyclic stability of printed tracks having excellent feature definition in combination with scalable ink production and adjustable rheology bring the high-volume manufacturing of stretchable wearables into scope.
| S-EPMC9477090 | biostudies-literature