Wearable Sensors Detect Movement Differences in the Portable Warrior Test of Tactical Agility After mTBI in Service Members

2021 ◽  
Author(s):  
Oleg Favorov ◽  
Olcay Kursun ◽  
Timothy Challener ◽  
Amy Cecchini ◽  
Karen L McCulloch

ABSTRACT Introduction Assessment of functional recovery of service members following a concussion is central to their return to duty. Practical military-relevant performance-based tests are needed for identifying those who might need specialized rehabilitation, for evaluating the progress of recovery, and for making return-to-duty determinations. One such recently developed test is the ‘Portable Warrior Test of Tactical Agility’ (POWAR-TOTAL) assessment designed for use following concussion in an active duty population. This agility task involves maneuvers used in military training, such as rapid stand-to-prone and prone-to-stand transitions, combat rolls, and forward and backward running. The effect of concussion on the performance of such maneuvers has not been established. Materials and Methods The Institutional Review Board–approved study was conducted at Ft. Bragg, North Carolina, on 57 healthy control (HC) service members (SMs) and 42 well-matched SMs who were diagnosed with concussion and were referred for physical therapy with the intent to return to duty. Each study participant performed five consecutive trials of the POWAR-TOTAL task at full exertion while wearing inertial sensors, which were used to identify the constituent task maneuvers, or phases, and measure their durations. Statistical analyses were performed on durations of three main phases: (1) rising from prone and running, (2) lowering from vertical to prone, and (3) combat rolls. Results None of the three phases showed significant correlation with age (range 18-45 years) in either group. Gradual improvement in all three phase durations across five trials was observed in the HC group, but not in the concussed group. On average, control subjects performed significantly faster (P < .004 or less) than concussed subjects in all trials in the lowering and rolling phases, but less so in the rising/running phase. Membership in the concussed group had a strong effect on the lowering phase (Cohen’s d = 1.05), medium effect on the rolling phase (d = 0.72), and small effect on the rising/running phase (d = 0.49). Individuals in the HC group who had a history of prior concussions were intermediate between the concussed group and the never-concussed group in the lowering and rolling phases. Duration of transitional movements (lowering from standing to prone and combat rolls) was better at differentiating individuals’ performance by group (receiver operating characteristic area under the curve [AUC] = 0.83) than the duration of the entire POWAR-TOTAL task (AUC = 0.71). Conclusions Inertial sensor analysis reveals that rapid transitional movements (such as lowering from vertical to prone position and combat rolls) are particularly discriminative between SMs recovering from concussion and their concussion-free peers. This analysis supports the validity of POWAR-TOTAL as a useful tool for therapists who serve military SMs.

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 82 ◽  
Author(s):  
Udeni Jayasinghe ◽  
William S. Harwin ◽  
Faustina Hwang

Inertial sensors are a useful instrument for long term monitoring in healthcare. In many cases, inertial sensor devices can be worn as an accessory or integrated into smart textiles. In some situations, it may be beneficial to have data from multiple inertial sensors, rather than relying on a single worn sensor, since this may increase the accuracy of the analysis and better tolerate sensor errors. Integrating multiple sensors into clothing improves the feasibility and practicality of wearing multiple devices every day, in approximately the same location, with less likelihood of incorrect sensor orientation. To facilitate this, the current work investigates the consequences of attaching lightweight sensors to loose clothes. The intention of this paper is to discuss how data from these clothing sensors compare with similarly placed body worn sensors, with additional consideration of the resulting effects on activity recognition. This study compares the similarity between the two signals (body worn and clothing), collected from three different clothing types (slacks, pencil skirt and loose frock), across multiple daily activities (walking, running, sitting, and riding a bus) by calculating correlation coefficients for each sensor pair. Even though the two data streams are clearly different from each other, the results indicate that there is good potential of achieving high classification accuracy when using inertial sensors in clothing.


Author(s):  
Tomás Pérez-Fernández ◽  
Susan Armijo-Olivo ◽  
Sonia Liébana ◽  
Pablo José de la Torre Ortíz ◽  
Josué Fernández-Carnero ◽  
...  

Abstract Background The craniocervical flexion test (CCFT) is recommended when examining patients with neck pain related conditions and as a deep cervical retraining exercise option. During the execution of the CCFT the examiner should visually assess that the amount of craniocervical flexion range of motion (ROM) progressively increases. However, this task is very subjective. The use of inertial wearable sensors may be a user-friendly option to measure and objectively monitor the ROM. The objectives of our study were (1) to measure craniocervical flexion range of motion (ROM) associated with each stage of the CCFT using a wearable inertial sensor and to determine the reliability of the measurements and (2) to determine craniocervical flexion ROM targets associated with each stage of the CCFT to standardize their use for assessment and training of the deep cervical flexor (DCF) muscles. Methods Adults from a university community able to successfully perform the CCFT participated in this study. Two independent examiners evaluated the CCFT in two separate sessions. During the CCFT, a small wireless inertial sensor was adhered to the centre of the forehead to provide real-time monitoring and to record craniocervical flexion ROM. The intra- and inter-rater reliability of the assessment of craniocervical ROM was calculated. This study was approved by the Research Ethics Committee of CEU San Pablo University (236/17/08). Results Fifty-six participants (18 males, 23 females; mean [SD] age, 21.8 [3.45] years) were included in the study and successfully completed the study protocol. All interclass correlation coefficient (ICC) values indicated good or excellent reliability of the assessment of craniocervical ROM using a wearable inertial sensor. There was high variability between subjects on the amount of craniocervical ROM necessary to achieve each stage of the CCFT. Conclusions The use of inertial sensors is a reliable method to measure the craniocervical flexion ROM associated with the CCFT. The great variability in the ROM limits the possibility to standardize a set of targets of craniocervical flexion ROM equivalent to each of the pressure targets of the pressure biofeedback unit.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254813
Author(s):  
Eloise V. Briggs ◽  
Claudia Mazzà

Detection of hoof-on and -off events are essential to gait classification in horses. Wearable sensors have been endorsed as a convenient alternative to the traditional force plate-based method. The aim of this study was to propose and validate inertial sensor-based methods of gait event detection, reviewing different sensor locations and their performance on different gaits and exercise surfaces. Eleven horses of various breeds and ages were recruited to wear inertial sensors attached to the hooves, pasterns and cannons. Gait events detected by pastern and cannon methods were compared to the reference, hoof-detected events. Walk and trot strides were recorded on asphalt, grass and sand. Pastern-based methods were found to be the most accurate and precise for detecting gait events, incurring mean errors of between 1 and 6ms, depending on the limb and gait, on asphalt. These methods incurred consistent errors when used to measure stance durations on all surfaces, with mean errors of 0.1 to 1.16% of a stride cycle. In conclusion, the methods developed and validated here will enable future studies to reliably detect equine gait events using inertial sensors, under a wide variety of field conditions.


2021 ◽  
Vol 11 ◽  
Author(s):  
Peter C. Fino ◽  
Margaret M. Weightman ◽  
Leland E. Dibble ◽  
Mark E. Lester ◽  
Carrie W. Hoppes ◽  
...  

Determining readiness for duty after mild traumatic brain injury (mTBI) is essential for the safety of service members and their unit. Currently, these decisions are primarily based on self-reported symptoms, objective measures that assess a single system, or standardized physical or cognitive tests that may be insensitive or lack ecological validity for warrior tasks. While significant technological advancements have been made in a variety of assessments of these individual systems, assessments of isolated tasks are neither diagnostically accurate nor representative of the demands imposed by daily life and military activities. Emerging evidence suggests that complex tasks, such as dual-task paradigms or turning, have utility in probing functional deficits after mTBI. Objective measures from turning tasks in single- or dual-task conditions, therefore, may be highly valuable for clinical assessments and return-to-duty decisions after mTBI. The goals of this study are to assess the diagnostic accuracy, predictive capacity, and responsiveness to rehabilitation of objective, dual-task turning measures within an mTBI population. These goals will be accomplished over two phases. Phase 1 will enroll civilians at three sites and active-duty service members at one site to examine the diagnostic accuracy and predictive capacity of dual-task turning outcomes. Phase 1 participants will complete a series of turning tasks while wearing inertial sensors and a battery of clinical questionnaires, neurocognitive testing, and standard clinical assessments of function. Phase 2 will enroll active-duty service members referred for rehabilitation from two military medical treatment facilities to investigate the responsiveness to rehabilitation of objective dual-task turning measures. Phase 2 participants will complete two assessments of turning while wearing inertial sensors: a baseline assessment prior to the first rehabilitation session and a post-rehabilitation assessment after the physical therapist determines the participant has completed his/her rehabilitation course. A variable selection procedure will then be implemented to determine the best task and outcome measure for return-to-duty decisions based on diagnostic accuracy, predictive capacity, and responsiveness to rehabilitation. Overall, the results of this study will provide guidance and potential new tools for clinical decisions in individuals with mTBI.Clinical Trial Registration: clinicaltrials.gov, Identifier NCT03892291.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jing Ye ◽  
Hui Wang ◽  
MeiJie Li ◽  
Ning Wang

Aerobics is the fusion of gymnastics, dance, and music; it is a body of a sports project, along with the development of the society. The growing demand for aerobics inevitably increases the demand for aerobics coach and teacher and has opened elective aerobics class which is an effective way of cultivating professional talents relevant to aerobics. Aerobics has extended fixed teaching mode and cannot conform to the development of the times. The motion prediction of aerobics athletes is a new set of teaching aid. In this paper, a motion prediction model of aerobics athletes is built based on the wearable inertial sensor of the Internet of Things and the bidirectional long short term memory (BiLSTM) network. Firstly, a wireless sensor network based on ZigBee was designed and implemented to collect the posture data of aerobics athletes. The inertial sensors were used for data collection and transmission of the data to the cloud platform through Ethernet. Then, the movement of aerobics athletes is recognized and predicted by the BiLSTM network. Based on the BiLSTM network and the attention mechanism, this paper proposes to solve the problem of low classification accuracy caused by the traditional method of directly summing and averaging the updated output vectors corresponding to each moment of the BiLSTM layer. The simulation experiment is also carried out in this paper. The experimental results show that the proposed model can recognize aerobics effectively.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ive Weygers ◽  
Manon Kok ◽  
Thomas Seel ◽  
Darshan Shah ◽  
Orçun Taylan ◽  
...  

AbstractSkin-attached inertial sensors are increasingly used for kinematic analysis. However, their ability to measure outside-lab can only be exploited after correctly aligning the sensor axes with the underlying anatomical axes. Emerging model-based inertial-sensor-to-bone alignment methods relate inertial measurements with a model of the joint to overcome calibration movements and sensor placement assumptions. It is unclear how good such alignment methods can identify the anatomical axes. Any misalignment results in kinematic cross-talk errors, which makes model validation and the interpretation of the resulting kinematics measurements challenging. This study provides an anatomically correct ground-truth reference dataset from dynamic motions on a cadaver. In contrast with existing references, this enables a true model evaluation that overcomes influences from soft-tissue artifacts, orientation and manual palpation errors. This dataset comprises extensive dynamic movements that are recorded with multimodal measurements including trajectories of optical and virtual (via computed tomography) anatomical markers, reference kinematics, inertial measurements, transformation matrices and visualization tools. The dataset can be used either as a ground-truth reference or to advance research in inertial-sensor-to-bone-alignment.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4033
Author(s):  
Peng Ren ◽  
Fatemeh Elyasi ◽  
Roberto Manduchi

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.


Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5167
Author(s):  
Nicky Baker ◽  
Claire Gough ◽  
Susan J. Gordon

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.


2021 ◽  
Author(s):  
Amy Seal Cecchini ◽  
Julianna Prim ◽  
Wanqing Zhang ◽  
Courtney H Harrison ◽  
Karen L McCulloch

ABSTRACT Introduction Return-to-duty (RTD) readiness assessment for service members (SM) following concussion requires complex clinical considerations. The Portable Warrior Test of Tactical Agility (POWAR-TOTAL) is a functional assessment which improves on previous laboratory-based RTD assessments. Methods Sixty-four SM diagnosed with concussion and 60 healthy control (HC) SM participated in this study. Group differences were analyzed to validate the POWAR-TOTAL. The High-level Mobility Assessment Test (HiMAT) was used to examine concurrent construct validity. An exploratory logistic regression analysis examined predictive validity. Results The groups were demographically well-matched except for educational level. POWAR-TOTAL measures were statistically significantly different between the groups with moderate to large effect sizes. Concussed participants were less likely to be able to complete all trials of the POWAR-TOTAL. Motor scores correlated highly with HiMAT scores. POWAR-TOTAL motor task performance and membership in the control group was significantly associated with self-reported physical readiness to deploy. Conclusion The POWAR-TOTAL is a clinically feasible, military relevant assessment that is sensitive to differences between concussed and HC SM. This analysis supports the discriminant and construct validity of the POWAR-TOTAL, and may be useful for medical providers evaluating RTD readiness for SM who have sustained a concussion.


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