On the Orientation Error of IMU: Investigating Static and Dynamic Accuracy Targeting Human Motion

Preliminary Validity and Acceptability of Motion Tape for Measuring Low Back Movement: Mixed Methods Study

BACKGROUND

Low back pain (LBP) is a significant public health problem that can result in physical disability and financial burden for the individual and society. Physical therapy is effective for managing LBP and includes evaluation of posture and movement, interventions directed at modifying posture and movement, and prescription of exercises. However, physical therapists have limited tools for objective evaluation of low back posture and movement and monitoring of exercises, and this evaluation is limited to the time frame of a clinical encounter. There is a need for a valid tool that can be used to evaluate low back posture and movement and monitor exercises outside the clinic. To address this need, a fabric-based, wearable sensor, Motion Tape (MT), was developed and adapted for a low back use case. MT is a low-profile, disposable, self-adhesive, skin-strain sensor developed by spray coating piezoresistive graphene nanocomposites directly onto commercial kinesiology tape.

OBJECTIVE

The objectives of this study were to (1) validate MT for measuring low back posture and movement and (2) assess the acceptability of MT for users.

METHODS

A total of 10 participants without LBP were tested. A 3D optical motion capture system was used as a reference standard to measure low back kinematics. Retroreflective markers and a matrix of MTs were placed on the low back to measure kinematics (motion capture) and strain (MT) simultaneously during low back movements in the sagittal, frontal, and axial planes. Cross-correlation coefficients were calculated to evaluate the concurrent validity of MT strain in reference motion capture kinematics during each movement. The acceptability of MT was assessed using semistructured interviews conducted with each participant after laboratory testing. Interview data were analyzed using rapid qualitative analysis to identify themes and subthemes of user acceptability.

RESULTS

Visual inspection of concurrent MT strain and kinematics of the low back indicated that MT can distinguish between different movement directions. Cross-correlation coefficients between MT strain and motion capture kinematics ranged from -0.915 to 0.983, and the strength of the correlations varied across MT placements and low back movement directions. Regarding user acceptability, participants expressed enthusiasm toward MT and believed that it would be helpful for remote interventions for LBP but provided suggestions for improvement.

CONCLUSIONS

MT was able to distinguish between different low back movements, and most MTs demonstrated moderate to high correlation with motion capture kinematics. This preliminary laboratory validation of MT provides a basis for future device improvements, which will also involve testing in a free-living environment. Overall, users found MT acceptable for use in physical therapy for managing LBP.

Real-Time Visual Feedback Based on MIMUs Technology Reduces Bowing Errors in Beginner Violin Students

Violin is one of the most complex musical instruments to learn. The learning process requires constant training and many hours of exercise and is primarily based on a student-teacher interaction where the latter guides the beginner through verbal instructions, visual demonstrations, and physical guidance. The teacher's instruction and practice allow the student to learn gradually how to perform the correct gesture autonomously. Unfortunately, these traditional teaching methods require the constant supervision of a teacher and the interpretation of non-real-time feedback provided after the performance. To address these limitations, this work presents a novel interface (Visual Interface for Bowing Evaluation-VIBE) to facilitate student's progression throughout the learning process, even in the absence of direct teacher intervention. The proposed interface allows two key parameters of bowing movements to be monitored, namely, the angle between the bow and the string (i.e., α angle) and the bow tilt (i.e., β angle), providing real-time visual feedback on how to correctly move the bow. Results collected on 24 beginners (12 exposed to visual feedback, 12 in a control group) showed a positive effect of the real-time visual feedback on the improvement of bow control. Moreover, the subjects exposed to visual feedback judged the latter as useful to correct their movement and clear in terms of the presentation of data. Although the task was rated as harder when performed with the additional feedback, the subjects did not perceive the presence of a violin teacher as essential to interpret the feedback.

Enhancing accuracy and convenience of golf swing tracking with a wrist-worn single inertial sensor

In this study, we address two technical challenges to enhance golf swing trajectory accuracy using a wrist-worn inertial sensor: orientation estimation and drift error mitigation. We extrapolated consistent sensor orientation from specific address-phase signal segments and trained the estimation with a convolutional neural network. We then mitigated drift error by applying a constraint on wrist speed at the address, backswing top, and finish, and ensuring that the wrist's finish displacement aligns with a virtual circle on the 3D swing plane. To verify the proposed methods, we gathered data from twenty male right-handed golfers, including professionals and amateurs, using a driver and a 7-iron. The orientation estimation error was about 60% of the baseline, comparable to studies requiring additional sensor information or calibration poses. The drift error was halved and the single-inertial-sensor tracking performance across all swing phases was about 17 cm, on par with multimodal approaches. This study introduces a novel signal processing method for tracking rapid, wide-ranging motions, such as a golf swing, while maintaining user convenience. Our results could impact the burgeoning field of daily motion monitoring for health care, especially with the increasing prevalence of wearable devices like smartwatches.

Physical Therapists' Acceptance of a Wearable, Fabric-Based Sensor System (Motion Tape) for Use in Clinical Practice: Qualitative Focus Group Study

BACKGROUND

Low back pain (LBP) is a costly global health condition that affects individuals of all ages and genders. Physical therapy (PT) is a commonly used and effective intervention for the management of LBP and incorporates movement assessment and therapeutic exercise. A newly developed wearable, fabric-based sensor system, Motion Tape, uses novel sensing and data modeling to measure lumbar spine movements unobtrusively and thus offers potential benefits when used in conjunction with PT. However, physical therapists' acceptance of Motion Tape remains unexplored.

OBJECTIVE

The primary aim of this research study was to evaluate physical therapists' acceptance of Motion Tape to be used for the management of LBP. The secondary aim was to explore physical therapists' recommendations for future device development.

METHODS

Licensed physical therapists from the American Physical Therapy Association Academy of Leadership Technology Special Interest Group participated in this study. Overall, 2 focus groups (FGs; N=8) were conducted, in which participants were presented with Motion Tape samples and examples of app data output on a poster. Informed by the Technology Acceptance Model, we conducted semistructured FGs and explored the wearability, usefulness, and ease of use of and suggestions for improvements in Motion Tape for PT management of LBP. FG data were transcribed and analyzed using rapid qualitative analysis.

RESULTS

Regarding wearability, participants perceived that Motion Tape would be able to adhere for several days, with some variability owing to external factors. Feedback was positive for the low-profile and universal fit, but discomfort owing to wires and potential friction with clothing was of concern. Other concerns included difficulty with self-application and potential skin sensitivity. Regarding usefulness, participants expressed that Motion Tape would enhance the efficiency and specificity of assessments and treatment. Regarding ease of use, participants stated that the app would be easy, but data management and challenges with interpretation were of concern. Physical therapists provided several recommendations for future design improvements including having a wireless system or removable wires, customizable sizes for the tape, and output including range of motion data and summary graphs and adding app features that consider patient input and context.

CONCLUSIONS

Several themes related to Motion Tape's wearability, usefulness, and ease of use were identified. Overall, physical therapists expressed acceptance of Motion Tape's potential for assessing and monitoring low back posture and movement, both within and outside clinical settings. Participants expressed that Motion Tape would be a valuable tool for the personalized treatment of LBP but highlighted several future improvements needed for Motion Tape to be used in practice.

Investigating concurrent validity of inertial sensors to evaluate multiplanar spine movement

Inertial measurement units (IMUs) offer a portable and inexpensive alternative to traditional optical motion capture systems, and have potential to support clinical diagnosis and treatment of low back pain; however, due to a lack of confidence regarding the validity of IMU-derived metrics, their uptake and acceptance remain a challenge. The objective of this work was to assess the concurrent validity of the Xsens DOT IMUs for tracking multiplanar spine movement, and to evaluate concurrent validity and reliability for estimating clinically relevant metrics relative to gold-standard optical motion capture equipment. Ten healthy controls performed spine range of motion (ROM) tasks, while data were simultaneously tracked from IMUs and optical marker clusters placed over the C7, T12, and S1 vertebrae. Root mean square error (RMSE), mean absolute error (MAE), and intraclass correlation coefficients (ICC2,1) were calculated to assess validity and reliability of absolute (abs; C7, T12, and S1 sensors) and relative joint (rel; intersegmental thoracic, lumbar, and total) motion. Overall RMSEabs = 1.33°, MAEabs = 0.74° ± 0.69, and ICC2,1,abs = 0.953 across all movements, sensors, and planes. Results were slightly better for uniplanar movements when evaluating the primary rotation axis (prim) absolute ROM (MAEabs,prim = 0.56° ± 0.49; ICC2,1,abs,prim = 0.999). Similarly, when evaluating relative intersegmental motion, overall RMSErel = 2.39°, MAErel = 1.10° ± 0.96, and ICC2,1,rel = 0.950, and relative primary rotation axis achieved MAErel,prim = 0.87° ± 0.77, and ICC2,1,rel,prim = 0.994. Findings from this study suggest that these IMUs can be considered valid for tracking multiplanar spine movement, and may be used to objectively assess spine movement and neuromuscular control in clinics.

A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders

In recent years the healthcare industry has had increased difficulty seeing all low-risk patients, including but not limited to suspected osteoarthritis (OA) patients. To help address the increased waiting lists and shortages of staff, we propose a novel method of automated biomarker identification and quantification for the monitoring of treatment or disease progression through the analysis of clinical motion data captured from a standard RGB video camera. The proposed method allows for the measurement of biomechanics information and analysis of their clinical significance, in both a cheap and sensitive alternative to the traditional motion capture techniques. These methods and results validate the capabilities of standard RGB cameras in clinical environments to capture clinically relevant motion data. Our method focuses on generating 3D human shape and pose from 2D video data via adversarial training in a deep neural network with a self-attention mechanism to encode both spatial and temporal information. Biomarker identification using Principal Component Analysis (PCA) allows the production of representative features from motion data and uses these to generate a clinical report automatically. These new biomarkers can then be used to assess the success of treatment and track the progress of rehabilitation or to monitor the progression of the disease. These methods have been validated with a small clinical study, by administering a local anaesthetic to a small population with knee pain, this allows these new representative biomarkers to be validated as statistically significant (p -value < 0.05 ). These significant biomarkers include the cumulative acceleration of elbow flexion/extension in a sit-to-stand, as well as the smoothness of the knee and elbow flexion/extension in both a squat and sit-to-stand.

A comparison of Expert and Novice marksmanship performance and postural mechanics using inertial measurement units (IMUs) during dynamic live-fire shooting

Marksmanship is a foundational Soldier skill required for all active-duty military personnel regardless of duty position. This research compared shooting performance and underlying postural mechanics of Expert and Novice marksmen during a dynamic, live-fire shooting task. Eighteen military personnel volunteered to participate in this study (n = 9 Experts and n = 9 Novices). All participants completed the dynamic marksmanship task with an M4 carbine under each of two equipment conditions: (I) a No Load Condition (6 kg) and (II) a Loaded Condition (31 kg) using standard-issue military equipment. Marksmanship performance was assessed using lethality measures including total hits and course efficiency. Postural mechanics were collected via body- and weapon-mounted inertial measurement units (IMUs). Significant differences (p < 0.05) in shooting performance and course efficiency were found between Expert and Novice marksmen for both load conditions. Significant differences were also found in postural movement patterns between Expert and Novice marksmen utilizing IMU-derived performance measures, especially when transitioning between targets, though these findings were not always consistent across load conditions. Based on these results, training interventions that focus on target acquisition, increasing torso stability, and maximizing the linkage between the torso and weapon could be recommended to improve performance in Novice marksmen.

Reliability and validity of estimated angles information assessed using inertial measurement unit-based motion sensors

BACKGROUND

Inertial measurement unit (IMU)-based motion sensors are affordable, and their use is appropriate for rehabilitation. However, regarding the accuracy of estimated angle information obtained from this sensor, it is reported that it is likely affected by velocity.

OBJECTIVE

The present study investigated the reliability and validity of the angle information obtained using IMU-based sensors compared with a three-dimensional (3D) motion analyzer.

METHODS

The Euler angle obtained using the 3D motion analyzer and the angle obtained using the IMU-based sensor (IMU angle) were compared. Reliability was assessed by comparing the Bland-Altman analysis, intra-class correlation coefficient (ICC) (1,1), and cross-correlation function. The root mean square (RMS) error, ICC (2,1), and cross-correlation function were used to compare data on the Euler and IMU angles to evaluate the validity.

RESULTS

Regarding reliability, the Bland-Atman analysis indicated no fixed or proportional bias in the angle measurements. The measurement errors ranged from 0.2° to 3.2°. In the validity, the RMS error ranged from 0.3° to 2.2°. The ICCs (2,1) were 0.9. The cross-correlation functions were >0.9, which indicated a high degree of agreement.

CONCLUSION

The IMU-based sensor had a high reliability and validity. The IMU angle may be used in rehabilitation.

Angle measurement stability and cycle counting accuracy of hours-long duration IMU based arm motion tracking with application to normal shoulder ADLs

BACKGROUND

Inertial measurement units are increasing used for monitoring joint motion, but there is a need to demonstrate their suitability during hours-long continuous use, as well as a need for validated methods to count arm cycles and provide descriptions of typical cycles.

RESEARCH QUESTION

Do IMU sensors and rainflow counting have sufficient accuracy for tracking and cycle counting of hours-long continuous arm motion? If so, what are the cycle rates of normal arm ADL and is there a representative cycle that can serve as a 'gait cycle' for the arm?

METHODS

IMU sensors continuously tracked a robot performing 8 h of simulated cyclic arm motion. Error in the angle measurements was regressed against time to determine the rate of error and the total accumulated error. Additionally, the cycle count accuracy of rainflow, peak/valley, and Fourier transform counting methods was evaluated.

RESULTS

Over 8 h the IMU measurements accumulated a maximum 0.473° of error and the rainflow method counted cycles with less than 1% error. Applying rainflow counting to normal shoulder ADL resulted in an average rate of 533 elevation cycles per day.Tabulating the ADL cycles by mean and range values into a matrix and calculating the centroid, the single best values representing arm elevation cycles were a mean of 22.4° and a range of 21.6°.

SIGNIFICANCE

IMU sensors can track arm motion for 8 h with little increase in error, though during longer durations error may reach unacceptable levels. For normal arm ADL, the rainflow determined count of arm elevation full-cycles differed from previous estimates based on peak/valley counting. From the rainflow counting, a single cycle representation of cycle mean and range was determined that can be used as a 'gait cycle' for the shoulder.

The Performance of Inertial Measurement Unit Sensors on Various Hardware Platforms for Binaural Head-Tracking Applications

Binaural synthesis with head tracking is often used in spatial audio systems. The devices used for head tracking must provide data on the orientation of the listener's head. These data need to be highly accurate, and they need to be provided as fast and as frequently as possible. Therefore, head-tracking devices need to be equipped with high-quality inertial measurement unit (IMU) sensors. Since IMUs readily include triaxial accelerometers, gyroscopes, and magnetometers, it is crucial that all of these sensors perform well, as the head orientation is calculated from all sensor outputs. This paper discusses the challenges encountered in the process of the performance assessment of IMUs through appropriate measurements. Three distinct hardware platforms were investigated: five IMU sensors either connected to Arduino-based embedded systems or being an integral part of one, five smartphones across a broad range of overall quality with integrated IMUs, and a commercial virtual reality unit that utilizes a headset with integrated IMUs. An innovative measurement method is presented and proposed for comparing the performance of sensors on all three platforms. The results of the measurements performed using the proposed method show that all three investigated platforms are adequate for the acquisition of the data required for calculating the orientation of a device as the input to the binaural synthesis process. Some limitations that have been observed during the measurements, regarding data acquisition and transfer, are discussed.

Concurrent validity of a custom computer vision algorithm for measuring lumbar spine motion from RGB-D camera depth data

Using RGB-D cameras as an alternative motion capture device can be advantageous for biomechanical spine motion assessments of movement quality and dysfunction due to their lower cost and complexity. In this study, we evaluated RGB-D camera performance relative to gold-standard optoelectronic motion capture equipment. Twelve healthy young adults (6M, 6F) were recruited to perform repetitive spine flexion-extension, while wearing infrared reflective marker clusters placed over their T₁₀-T₁₂ spinous processes and sacrum, and motion capture data were recorded simultaneously by both systems. Custom computer vision algorithms were developed to extract spine angles from depth data. Root mean square error (RMSE) was calculated for continuous Euler angles, and intraclass correlation coefficients (ICC_2,1) were calculated between minimum and maximum angles and range of motion in all movement planes. RMSE was low (RMSE ≤ 2.05°) and reliability was good to excellent (0.849 ≤ ICC_2,1 ≤ 0.979) across all movement planes. In conclusion, the proposed algorithm for tracking 3D lumbar spine motion during a sagittal movement task from one RGB-D camera is reliable in comparison to gold-standard motion tracking equipment. Future research will investigate accuracy and validity in a wider variety of movements, and will also investigate the development of novel methods to measure spine motion without using infrared reflective markers.

Extension of the Rigid-Constraint Method for the Heuristic Suboptimal Parameter Tuning to Ten Sensor Fusion Algorithms Using Inertial and Magnetic Sensing

The orientation of a magneto-inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine-tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold-standard technology. To overcome this limitation, a Rigid-Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single-parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online.

Inertial Measurement Unit Sensors in Assistive Technologies for Visually Impaired People, a Review

A diverse array of assistive technologies have been developed to help Visually Impaired People (VIP) face many basic daily autonomy challenges. Inertial measurement unit sensors, on the other hand, have been used for navigation, guidance, and localization but especially for full body motion tracking due to their low cost and miniaturization, which have allowed the estimation of kinematic parameters and biomechanical analysis for different field of applications. The aim of this work was to present a comprehensive approach of assistive technologies for VIP that include inertial sensors as input, producing results on the comprehension of technical characteristics of the inertial sensors, the methodologies applied, and their specific role in each developed system. The results show that there are just a few inertial sensor-based systems. However, these sensors provide essential information when combined with optical sensors and radio signals for navigation and special application fields. The discussion includes new avenues of research, missing elements, and usability analysis, since a limitation evidenced in the selected articles is the lack of user-centered designs. Finally, regarding application fields, it has been highlighted that a gap exists in the literature regarding aids for rehabilitation and biomechanical analysis of VIP. Most of the findings are focused on navigation and obstacle detection, and this should be considered for future applications.

The assessment of center of mass and center of pressure during quiet stance: Current applications and future directions

This perspective article provides a brief review of our understanding of how center of pressure (CoP) and center of mass (CoM) are traditionally utilized to measure quiet standing and how technological advancements are allowing for measurements to be derived outside the confines of a laboratory setting. Furthermore, this viewpoint provides descriptions of what CoP and CoM outcomes may reflect, a discussion of recent developments in selected balance outcomes, the importance of measuring instantaneous balance outcomes, and directions for future questions/research. Considering the enormous number and cost of falls annually, conclusions drawn from this perspective underscore the need for more cohesive efforts to advance our understanding of balance performance. As we refine the technology and algorithms used to portably assess postural stability, the question of which measurement (i.e. CoP or CoM) to utilize seems to be highly dependent on the question being asked. Further, the complexity of the question appears to span multiple disciplines and cultivate exploration of the intrinsic mechanisms of stability. Recently developed multi-dimensional methods for assessing balance performance may provide additional insight into balance, improving our ability to predict balance impairments and falls outside the laboratory and in the clinic. However, additional work will be necessary to understand the clinical significance and predictive capacity of these outcomes in various fall-prone populations.

Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

The orientation of a magneto and inertial measurement unit (MIMU) is estimated by means of sensor fusion algorithms (SFAs) thus enabling human motion tracking. However, despite several SFAs implementations proposed over the last decades, there is still a lack of consensus about the best performing SFAs and their accuracy. As suggested by recent literature, the filter parameters play a central role in determining the orientation errors. The aim of this work is to analyze the accuracy of ten SFAs while running under the best possible conditions (i.e., their parameter values are set using the orientation reference) in nine experimental scenarios including three rotation rates and three commercial products. The main finding is that parameter values must be specific for each SFA according to the experimental scenario to avoid errors comparable to those obtained when the default parameter values are used. Overall, when optimally tuned, no statistically significant differences are observed among the different SFAs in all tested experimental scenarios and the absolute errors are included between 3.8 deg and 7.1 deg. Increasing the rotation rate generally leads to a significant performance worsening. Errors are also influenced by the MIMU commercial model. SFA MATLAB implementations have been made available online.

Dynamic Joint Motions in Occupational Environments as Indicators of Potential Musculoskeletal Injury Risk

The objective of this study was to test the feasibility of using a pair of wearable inertial measurement unit (IMU) sensors to accurately capture dynamic joint motion data during simulated occupational conditions. Eleven subjects (5 males and 6 females) performed repetitive neck, low-back, and shoulder motions simulating low- and high-difficulty occupational tasks in a laboratory setting. Kinematics for each of the 3 joints were measured via IMU sensors in addition to a "gold standard" passive marker optical motion capture system. The IMU accuracy was benchmarked relative to the optical motion capture system, and IMU sensitivity to low- and high-difficulty tasks was evaluated. The accuracy of the IMU sensors was found to be very good on average, but significant positional drift was observed in some trials. In addition, IMU measurements were shown to be sensitive to differences in task difficulty in all 3 joints (P < .05). These results demonstrate the feasibility for using wearable IMU sensors to capture kinematic exposures as potential indicators of occupational injury risk. Velocities and accelerations demonstrate the most potential for developing risk metrics since they are sensitive to task difficulty and less sensitive to drift than rotational position measurements.

Comparisons of physical exposure between workers harvesting apples on mobile orchard platforms and ladders, part 1: Back and upper arm postures

This study compared farmworkers' exposure to non-neutral postures using a new mobile platform apple harvesting method and the traditional method using ladders. Twenty-four workers were recruited and assigned into three groups: ladder workers (n = 8) picking apples from full trees using a ladder, mobile platform workers (n = 8) picking apples from upper part of the trees while standing on a moving platform, and ground-based mobile platform workers (n = 8) picking apples from lower part of the trees which the mobile platform workers left out. Upper arm and back inclinations were continuously monitored during harvesting using tri-axial accelerometers over full work shifts (~8 h). Upper arm posture was characterized as the percentage of time that upper arm flexion and abduction exceeded 30°, 60°, and 90°. Back posture was characterized as the percentage of time that torso angles (sagittal flexion or lateral bending) exceeded 10°, 20°, and 30°. The 10th, 50th, and 90th postural percentiles were also calculated. The platform workers had lower exposures to upper arm flexion and abduction than the ground and ladder workers. There were no differences in torso angles between the ladder and mobile platform workers; however, the ground workers were exposed to more and greater percentages of time in torso flexions.

Measuring upper arm elevation using an inertial measurement unit: An exploration of sensor fusion algorithms and gyroscope models

Many sensor fusion algorithms for analyzing human motion information collected with inertial measurement units have been reported in the scientific literature. Selecting which algorithm to use can be a challenge for ergonomists that may be unfamiliar with the strengths and limitations of the various options. In this paper, we describe fundamental differences among several algorithms, including differences in sensor fusion approach (e.g., complementary filter vs. Kalman Filter) and gyroscope error modeling (i.e., inclusion or exclusion of gyroscope bias). We then compare different sensor fusion algorithms considering the fundamentals discussed using laboratory-based measurements of upper arm elevation collected under three motion speeds. Results indicate peak displacement errors of <4.5° with a computationally efficient, non-proprietary complementary filter that did not account for gyroscope bias during each of the one-minute trials. Controlling for gyroscope bias reduced peak displacement errors to <3.0°. The complementary filters were comparable (<1° peak displacement difference) to the more complex Kalman filters.

Evaluation of Inertial Sensor Data by a Comparison with Optical Motion Capture Data of Guitar Strumming Gestures

Computing technologies have opened up a myriad of possibilities for expanding the sonic capabilities of acoustic musical instruments. Musicians nowadays employ a variety of rather inexpensive, wireless sensor-based systems to obtain refined control of interactive musical performances in actual musical situations like live music concerts. It is essential though to clearly understand the capabilities and limitations of such acquisition systems and their potential influence on high-level control of musical processes. In this study, we evaluate one such system composed of an inertial sensor (MetaMotionR) and a hexaphonic nylon guitar for capturing strumming gestures. To characterize this system, we compared it with a high-end commercial motion capture system (Qualisys) typically used in the controlled environments of research laboratories, in two complementary tasks: comparisons of rotational and translational data. For the rotations, we were able to compare our results with those that are found in the literature, obtaining RMSE below 10° for 88% of the curves. The translations were compared in two ways: by double derivation of positional data from the mocap and by double integration of IMU acceleration data. For the task of estimating displacements from acceleration data, we developed a compensative-integration method to deal with the oscillatory character of the strumming, whose approximative results are very dependent on the type of gestures and segmentation; a value of 0.77 was obtained for the average of the normalized covariance coefficients of the displacement magnitudes. Although not in the ideal range, these results point to a clearly acceptable trade-off between the flexibility, portability and low cost of the proposed system when compared to the limited use and cost of the high-end motion capture standard in interactive music setups.

Validation of Spatiotemporal and Kinematic Measures in Functional Exercises Using a Minimal Modeling Inertial Sensor Methodology

This study proposes a minimal modeling magnetic, angular rate and gravity (MARG) methodology for assessing spatiotemporal and kinematic measures of functional fitness exercises. Thirteen healthy persons performed repetitions of the squat, box squat, sandbag pickup, shuffle-walk, and bear crawl. Sagittal plane hip, knee, and ankle range of motion (ROM) and stride length, stride time, and stance time measures were compared for the MARG method and an optical motion capture (OMC) system. The root mean square error (RMSE), mean absolute percentage error (MAPE), and Bland–Altman plots and limits of agreement were used to assess agreement between methods. Hip and knee ROM showed good to excellent agreement with the OMC system during the squat, box squat, and sandbag pickup (RMSE: 4.4–9.8°), while ankle ROM agreement ranged from good to unacceptable (RMSE: 2.7–7.2°). Unacceptable hip and knee ROM agreement was observed for the shuffle-walk and bear crawl (RMSE: 3.3–8.6°). The stride length, stride time, and stance time showed good to excellent agreement between methods (MAPE: (3.2 ± 2.8)%–(8.2 ± 7.9)%). Although the proposed MARG-based method is a valid means of assessing spatiotemporal and kinematic measures during various exercises, further development is required to assess the joint kinematics of small ROM, high velocity movements.

Using accelerations of single inertial measurement units to determine the intensity level of light-moderate-vigorous physical activities: Technical and mathematical considerations

Quantifying physical activity and estimating the metabolic equivalent of tasks based on inertial measurement units has led to the emergence of multiple methods and data reduction approaches known as physical activity metrics. The present study aims to compare those metrics and reduction approaches based on descriptive and high order statistics. Data were obtained from 147 young healthy subjects wearing inertial measurement units at their wrist or ankle during standing, walking and running, labeled as light, medium or vigorous activities. The research question was, first, if those metrics allowed differentiating between light, moderate, and vigorous physical activities, and, secondly, what was the relationship with the metabolic equivalent of the task performed. The results showed that each metric differentiated the level of activity and presented a high correlation with the metabolic equivalent of the task. However, each metric and data reduction approach demonstrated its specific statistical characteristics related to the localization of the sensors. Our findings also confirm the absolute necessity to detail explicitly all calculus and post processing of metrics in order to quantify the level of activity by inertial measurement units.

Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison

BACKGROUND

Emerging sensing and communication technologies are contributing to the development of many motor rehabilitation programs outside the standard healthcare facilities. Nowadays, motor rehabilitation exercises can be easily performed and monitored even at home by a variety of motion-tracking systems. These are cheap, reliable, easy-to-use, and allow also remote configuration and control of the rehabilitation programs. The two most promising technologies for home-based motor rehabilitation programs are inertial wearable sensors and video-based motion capture systems.

METHODS

In this paper, after a thorough review of the relevant literature, an original experimental analysis is reported for two corresponding commercially available solutions, a wearable inertial measurement unit and the Kinect, respectively. For the former, a number of different algorithms for rigid body pose estimation from sensor data were also tested. Both systems were compared with the measurements obtained with state-of-the-art marker-based stereophotogrammetric motion analysis, taken as a gold-standard, and also evaluated outside the lab in a home environment.

RESULTS

The results in the laboratory setting showed similarly good performance for the elementary large motion exercises, with both systems having errors in the 3-8 degree range. Usability and other possible limitations were also assessed during utilization at home, which revealed additional advantages and drawbacks for the two systems.

CONCLUSIONS

The two evaluated systems use different technology and algorithms, but have similar performance in terms of human motion tracking. Therefore, both can be adopted for monitoring home-based rehabilitation programs, taking adequate precautions however for operation, user instructions and interpretation of the results.

Accuracy of the Orientation Estimate Obtained Using Four Sensor Fusion Filters Applied to Recordings of Magneto-Inertial Sensors Moving at Three Rotation Rates

Magneto-Inertial technology is a well-established alternative to optical motion capture for human motion analysis applications since it allows prolonged monitoring in free-living conditions. Magneto and Inertial Measurement Units (MIMUs) integrate a triaxial accelerometer, a triaxial gyroscope and a triaxial magnetometer in a single and lightweight device. The orientation of the body to which a MIMU is attached can be obtained by combining its sensor readings within a sensor fusion framework. Despite several sensor fusion implementations have been proposed, no well-established conclusion about the accuracy level achievable with MIMUs has been reached yet. The aim of this preliminary study was to perform a direct comparison among four popular sensor fusion algorithms applied to the recordings of MIMUs rotating at three different rotation rates, with the orientation provided by a stereophotogrammetric system used as a reference. A procedure for suboptimal determination of the parameter filter values was also proposed. The findings highlighted that all filters exhibited reasonable accuracy (rms errors <; 6.4°). Moreover, in accordance with previous studies, every algorithm's accuracy worsened as the rotation rate increased. At the highest rotation rate, the algorithm from Sabatini (2011) showed the best performance with errors smaller than 4.1° rms.

Development of a Post-stroke Upper Limb Rehabilitation Wearable Sensor for Use in Sub-Saharan Africa: A Pilot Validation Study

The development of context-appropriate sensor technologies could alleviate the significant burden of stroke in Sub-Saharan African rehabilitation clinicians and health care facilities. However, many commercially available wearable sensors are beyond the financial capabilities of the majority of African persons. In this study, we evaluated the concurrent validity of a low-cost wearable sensor (i.e., the outREACH sensor) to measure upper limb movement kinematics of 31 healthy persons, using an 8-camera Vicon motion capture system as the reference standard. The outREACH sensor showed high correlation (r range: 0.808-0.990) and agreement (mean difference range: -1.60 to 1.10) with the reference system regardless of task or kinematic parameter. Moreover, Bland-Altman analyses indicated that there were no significant systematic errors present. This study indicates that upper limb movement kinematics can be accurately measured using the outREACH sensor, and have the potential to enhance stroke evaluation and rehabilitation in sub-Saharan Africa.

Assessment of the Accuracy of Determining the Angular Position of the Unmanned Bathymetric Surveying Vehicle Based on the Sea Horizon Image

The paper presents the results of research on assessing the accuracy of angular position measurement relative to the sea horizon using a camera mounted on an unmanned bathymetric surveying vehicle of the Unmanned Surface Vehicle (USV) or Unmanned Aerial Vehicle (UAV) type. The first part of the article presents the essence of the problem. The rules of taking the angular position of the vehicle into account in bathymetric surveys and the general concept of the two-camera tilt compensator were described. The second part presents a mathematical description of the meters characterizing a resolution and a mean error of measurements, made on the base of the horizon line image, recorded with an optical system with a Complementary Metal-Oxide Semiconductor (CMOS) matrix. The phenomenon of the horizon line curvature in the image projected onto the matrix that appears with the increase of the camera height has been characterized. The third part contains an example of a detailed analysis of selected cameras mounted on UAVs manufactured by DJI, carried out using the proposed meters. The obtained results including measurement resolutions of a single-pixel and mean errors of the horizon line slope measurement were presented in the form of many tables and charts with extensive comments. The final part presents the general conclusions from the performed research and a proposal of directions for their further development.

Validation of Wearable Sensors during Team Sport-Specific Movements in Indoor Environments

The aim of this study was to determine possible influences, including data processing and sport-specific demands, on the validity of acceleration measures by an inertial measurement unit (IMU) in indoor environments. IMU outputs were compared to a three-dimensional (3D) motion analysis (MA) system and processed with two sensor fusion algorithms (Kalman filter, KF; Complementary filter, CF) at temporal resolutions of 100, 10, and 5 Hz. Athletes performed six team sport-specific movements whilst wearing a single IMU. Mean and peak acceleration magnitudes were analyzed. Over all trials (n = 1093), KF data overestimated MA resultant acceleration by 0.42 ± 0.31 m∙s⁻² for mean and 4.18 ± 3.68 m∙s⁻² for peak values, while CF processing showed errors of up to 0.57 ± 0.41 m∙s⁻² and −2.31 ± 2.25 m∙s⁻², respectively. Resampling to 5 Hz decreased the absolute error by about 14% for mean and 56% for peak values. Still, higher acceleration magnitudes led to a large increase in error. These results indicate that IMUs can be used for assessing accelerations in indoor team sports with acceptable means. Application of a CF and resampling to 5 Hz is recommended. High-acceleration magnitudes impair validity to a large degree and should be interpreted with caution.

Toward real-world evaluations of trunk exoskeletons using inertial measurement units

Trunk exoskeletons are an emerging technology that could reduce spinal loading, guide trunk motion, and augment lifting ability. However, while they have achieved promising results in brief laboratory studies, they have not yet been tested in longer-term real-world studies - partially due to reliance on stationary sensors such as cameras. To enable future real-world evaluations of trunk exoskeletons, this paper describes two preliminary studies on using inertial measurement units (IMUs) to collect kinematic data from an exoskeleton wearer. In the first study, a participant performed three activities (walking, sit-to-stand, box lifting) while trunk flexion angle was measured with both IMUs and reference cameras. The mean absolute difference in flexion angle between the two methods was 1.4° during walking, 3.6° during sit-to-stand and 5.2° during box lifting, showing that IMUs can measure trunk flexion with a reasonable accuracy. In the second study, six participants performed five activities (standing, sitting straight, slouching, 'good' lifting, 'bad' lifting), and a naïve Bayes classifier was used to automatically classify the activity from IMU data. The classification accuracy was 92.2%, indicating the feasibility of automated activity classification using IMUs. The IMUs will next be used to obtain longer-term recordings of different activities performed both with and without a trunk exoskeleton to determine how the exoskeleton affects a person's posture and behavior.

A feasibility study comparing objective and subjective field-based physical exposure measurements during apple harvesting with ladders and mobile platforms

Although mobile orchardplatforms have been developed to improve apple harvesting productivity in the US, the physical exposures of workers usingthe mobile platforms have not been well characterized, partlydue to the lack of assessment tools specific to the tree fruitorchard environment. The purpose of this study was to evaluate the feasibility and utility of different subjective and objective methods for characterizing apple harvesting workers' posture, armrepetition, heart rate, and perceived exertion during platform- and conventional ladder-based harvesting. During a regular full shiftwork (8 hours), the objective physical exposure measures (armelevation, torso inclination, and heart rate) of 6 platform, 6 ground, and 8 ladder workers were measured with tri-axial accelerometersand heart rate monitor; and subjective perceived exertion wascollected using standardized Borg RPE and CR-10 scales, translated into Spanish. The results showed that the arm elevation, torso forward bending, repetitiveness, heart rates, and perceived exertions were lower for the platform-based workers than forthe ladder-based workers. The subjective measures (Borg RPE and Borg CR-10) appeared to be similar and mirror the general trends of the objective heart rate and posture measures.These results indicate the potential benefit of these low-cost subjective measures when direct measurements are too costly,complicated, or not permitted. This study determined that field measurements of objective and subjective physical exposures were feasible for evaluating apple harvesting work. In summary, all themethods used appear to be feasible for field use in orchard-based environments..

Measurement of Upper Limb Range of Motion Using Wearable Sensors: A Systematic Review

Background

Wearable sensors are portable measurement tools that are becoming increasingly popular for the measurement of joint angle in the upper limb. With many brands emerging on the market, each with variations in hardware and protocols, evidence to inform selection and application is needed. Therefore, the objectives of this review were related to the use of wearable sensors to calculate upper limb joint angle. We aimed to describe (i) the characteristics of commercial and custom wearable sensors, (ii) the populations for whom researchers have adopted wearable sensors, and (iii) their established psychometric properties.

Methods

A systematic review of literature was undertaken using the following data bases: MEDLINE, EMBASE, CINAHL, Web of Science, SPORTDiscus, IEEE, and Scopus. Studies were eligible if they met the following criteria: (i) involved humans and/or robotic devices, (ii) involved the application or simulation of wearable sensors on the upper limb, and (iii) calculated a joint angle.

Results

Of 2191 records identified, 66 met the inclusion criteria. Eight studies compared wearable sensors to a robotic device and 22 studies compared to a motion analysis system. Commercial (n = 13) and custom (n = 7) wearable sensors were identified, each with variations in placement, calibration methods, and fusion algorithms, which were demonstrated to influence accuracy.

Conclusion

Wearable sensors have potential as viable instruments for measurement of joint angle in the upper limb during active movement. Currently, customised application (i.e. calibration and angle calculation methods) is required to achieve sufficient accuracy (error <  5°). Additional research and standardisation is required to guide clinical application.

Trial Registration

This systematic review was registered with PROSPERO (CRD42017059935).

An instrumented glove for monitoring hand function

The measurement of hand kinematics is important for the assessment and rehabilitation of the paralysed hand. The traditional method of hand function assessment uses a mechanical or electronic goniometer placed across the joint of interest to measure the range of joint movement. Mechanical goniometers are imprecise and lack the ability to provide a dynamic measurement; electronic goniometers are expensive and cumbersome to use during therapy. An alternative to the goniometric based assessment is to use inertial motion sensors to monitor the hand movement-these can be incorporated in a glove. In this paper, we present the design of an instrumented glove equipped with Magnetic, Angular Rate and Gravity (MARG) sensors for the objective evaluation of hand function. The instrumented glove presented in this paper is designed to assess the range of movement of the hand and also monitor the hand function during the course of hand rehabilitation. Static and dynamic calibrations were performed for the Euler angles calculated from the MARG sensors. The results are also presented for physiological flexion/extension of the wrist (relative roll), flexion/extension of elbow (relative pitch), and internal rotation/external rotation (relative yaw). The static calibration results gave mean absolute errors of 4.1° for roll, 4.0° for pitch, and 4.6° for yaw. From the dynamic calibration, the speed of response to a step change gave a convergence time of 0.4 s; sinusoidally oscillating movement gave good tracking at 0.2 Hz but exhibits overshoot errors at higher frequencies which were tested to be 1 Hz. We present the results of the calibration of the instrumented glove (one sensor pair measuring one joint angle) measuring anatomical joint angles-mean absolute errors during static calibration: 6.3° for a relative roll (wrist flexion/extension), 5.0° for relative pitch (elbow flexion/extension), and 4.5° for relative yaw (shoulder internal rotation/external rotation). The experimental results from the instrumented glove are promising, and it can be used as an alternative to the traditional goniometer based hand function assessments.

Validation of a Lower Back "Wearable"-Based Sit-to-Stand and Stand-to-Sit Algorithm for Patients With Parkinson's Disease and Older Adults in a Home-Like Environment

Introduction: Impaired sit-to-stand and stand-to-sit movements (postural transitions, PTs) in patients with Parkinson's disease (PD) and older adults (OA) are associated with risk of falling and reduced quality of life. Inertial measurement units (IMUs, also called "wearables") are powerful tools to monitor PT kinematics. The purpose of this study was to develop and validate an algorithm, based on a single IMU positioned at the lower back, for PT detection and description in the above-mentioned groups in a home-like environment. Methods: Four PD patients (two with dyskinesia) and one OA served as algorithm training group, and 21 PD patients (16 without and 5 with dyskinesia) and 11 OA served as test group. All wore an IMU on the lower back and were videotaped while performing everyday activities for 90-180 min in a non-standardized home-like environment. Accelerometer and gyroscope signals were analyzed using discrete wavelet transformation (DWT), a six degrees-of-freedom (DOF) fusion algorithm and vertical displacement estimation. Results: From the test group, 1,001 PTs, defined by video reference, were analyzed. The accuracy of the algorithm for the detection of PTs against video observation was 82% for PD patients without dyskinesia, 47% for PD patients with dyskinesia and 85% for OA. The overall accuracy of the PT direction detection was comparable across groups and yielded 98%. Mean PT duration values were 1.96 s for PD patients and 1.74 s for OA based on the algorithm (p < 0.001) and 1.77 s for PD patients and 1.51 s for OA based on clinical observation (p < 0.001). Conclusion: Validation of the PT detection algorithm in a home-like environment shows acceptable accuracy against the video reference in PD patients without dyskinesia and controls. Current limitations are the PT detection in PD patients with dyskinesia and the use of video observation as the video reference. Potential reasons are discussed.

A Wearable System for Real-Time Continuous Monitoring of Physical Activity

Over the last decades, wearable systems have gained interest for monitoring of physiological variables, promoting health, and improving exercise adherence in different populations ranging from elite athletes to patients. In this paper, we present a wearable system for the continuous real-time monitoring of respiratory frequency (f_R), heart rate (HR), and movement cadence during physical activity. The system has been experimentally tested in the laboratory (by simulating the breathing pattern with a mechanical ventilator) and by collecting data from one healthy volunteer. Results show the feasibility of the proposed device for real-time continuous monitoring of f_R, HR, and movement cadence both in resting condition and during activity. Finally, different synchronization techniques have been investigated to enable simultaneous data collection from different wearable modules.

Player Monitoring in Indoor Team Sports: Concurrent Validity of Inertial Measurement Units to Quantify Average and Peak Acceleration Values

The increasing interest in assessing physical demands in team sports has led to the development of multiple sports related monitoring systems. Due to technical limitations, these systems primarily could be applied to outdoor sports, whereas an equivalent indoor locomotion analysis is not established yet. Technological development of inertial measurement units (IMU) broadens the possibilities for player monitoring and enables the quantification of locomotor movements in indoor environments. The aim of the current study was to validate an IMU measuring by determining average and peak human acceleration under indoor conditions in team sport specific movements. Data of a single wearable tracking device including an IMU (Optimeye S5, Catapult Sports, Melbourne, Australia) were compared to the results of a 3D motion analysis (MA) system (Vicon Motion Systems, Oxford, UK) during selected standardized movement simulations in an indoor laboratory (n = 56). A low-pass filtering method for gravity correction (LF) and two sensor fusion algorithms for orientation estimation [Complementary Filter (CF), Kalman-Filter (KF)] were implemented and compared with MA system data. Significant differences (p < 0.05) were found between LF and MA data but not between sensor fusion algorithms and MA. Higher precision and lower relative errors were found for CF (RMSE = 0.05; CV = 2.6%) and KF (RMSE = 0.15; CV = 3.8%) both compared to the LF method (RMSE = 1.14; CV = 47.6%) regarding the magnitude of the resulting vector and strongly emphasize the implementation of orientation estimation to accurately describe human acceleration. Comparing both sensor fusion algorithms, CF revealed slightly lower errors than KF and additionally provided valuable information about positive and negative acceleration values in all three movement planes with moderate to good validity (CV = 3.9 – 17.8%). Compared to x- and y-axis superior results were found for the z-axis. These findings demonstrate that IMU-based wearable tracking devices can successfully be applied for athlete monitoring in indoor team sports and provide potential to accurately quantify accelerations and decelerations in all three orthogonal axes with acceptable validity. An increase in accuracy taking magnetometers in account should be specifically pursued by future research.

Accuracy of angular displacements and velocities from inertial-based inclinometers

The objective of this study was to evaluate the accuracy of various sensor fusion algorithms for measuring upper arm elevation relative to gravity (i.e., angular displacement and velocity summary measures) across different motion speeds. Thirteen participants completed a cyclic, short duration, arm-intensive work task that involved transfering wooden dowels at three work rates (slow, medium, fast). Angular displacement and velocity measurements of upper arm elevation were simultaneously measured using an inertial measurement unit (IMU) and an optical motion capture (OMC) system. Results indicated that IMU-based inclinometer solutions can reduce root-mean-square errors in comparison to accelerometer-based inclination estimates by as much as 87%, depending on the work rate and sensor fusion approach applied. The findings suggest that IMU-based inclinometers can substantially improve inclinometer accuracy in comparison to traditional accelerometer-based inclinometers. Ergonomists may use the non-proprietary sensor fusion algorithms provided here to more accurately estimate upper arm elevation.

Quantification and visualization of coordination during non-cyclic upper extremity motion

There are many design challenges in creating at-home tele-monitoring systems that enable quantification and visualization of complex biomechanical behavior. One such challenge is robustly quantifying joint coordination in a way that is intuitive and supports clinical decision-making. This work defines a new measure of coordination called the relative coordination metric (RCM) and its accompanying normalization schemes. RCM enables quantification of coordination during non-constrained discrete motions. Here RCM is applied to a grasping task. Fifteen healthy participants performed a reach, grasp, transport, and release task with a cup and a pen. The measured joint angles were then time-normalized and the RCM time-series were calculated between the shoulder-elbow, shoulder-wrist, and elbow-wrist. RCM was normalized using four differing criteria: the selected joint degree of freedom, angular velocity, angular magnitude, and range of motion. Percent time spent in specified RCM ranges was used asa composite metric and was evaluated for each trial. RCM was found to vary based on: (1) chosen normalization scheme, (2) the stage within the task, (3) the object grasped, and (4) the trajectory of the motion. The RCM addresses some of the limitations of current measures of coordination because it is applicable to discrete motions, does not rely on cyclic repetition, and uses velocity-based measures. Future work will explore clinically relevant differences in the RCM as it is expanded to evaluate different tasks and patient populations.

The Use of IMMUs in a Water Environment: Instrument Validation and Application of 3D Multi-Body Kinematic Analysis in Medicine and Sport

The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic field in the swimming pool and to identify the best volume for experimental test acquisition with a mean dynamic orientation error lower than 5°. Successively, the gait and the swimming analyses were explored in terms of spatiotemporal and joint kinematics variables. The extraction of only spatiotemporal parameters highlighted several critical issues and the joint kinematic information has shown to be an added value for both rehabilitative and sport training purposes. Furthermore, 3D joint kinematics applied using the IMMUs provided similar quantitative information than that of more expensive and bulky systems but with a simpler and faster setup preparation, a lower time consuming processing phase, as well as the possibility to record and analyze a higher number of strides/strokes without limitations imposed by the cameras.

Effects of Movement Speed and Magnetic Disturbance on the Accuracy of Inertial Measurement Units

This study evaluated the effects of motion speed and magnetic disturbance on the spatial orientation accuracy of an inertial measurement unit (IMU) on the hand. Thirteen participants performed six trials of a repetitive material transfer task. Movement speed (15, 30, 45 transfers/minute) and magnetic disturbance (absent, present) were the independent variables. Optical motion capture was the reference. Root-mean-square differences (RMSD) exceeded 20° when inclination measurements (pitch and roll) were calculated using the IMU accelerometer. A linear Kalman filter and a proprietary, embedded Kalman filter reduced inclination RMSD to <3° across all movement speeds. The RMSD in the heading direction (i.e., about gravity) increased (from <5° to 17°) under magnetic disturbance. The linear Kalman filter and the embedded Kalman filter reduced heading RMSD to <12° and <7°, respectively. Use of IMUs and Kalman filters can improve inclinometer measurement accuracy. However, magnetic disturbances continue to limit the accuracy of three-dimensional IMU motion capture.