scholarly journals A Pilot Study to Assess the Reliability of Sensing Joint Acoustic Emissions of the Wrist

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4240
Author(s):  
Daniel M. Hochman ◽  
Sevda Gharehbaghi ◽  
Daniel C. Whittingslow ◽  
Omer T. Inan
Keyword(s):  
Acoustic Emission ◽  
Signal To Noise Ratio ◽  
Intraclass Correlation ◽  
Acoustic Emissions ◽  
Wrist Flexion ◽  
Audio Features ◽  
Flexion Extension ◽  
Joint Health ◽  
Acoustic Emission Sensing ◽  
Future Work

Joint acoustic emission (JAE) sensing has recently proven to be a viable technique for non-invasive quantification indicating knee joint health. In this work, we adapt the acoustic emission sensing method to measure the JAEs of the wrist—another joint commonly affected by injury and degenerative disease. JAEs of seven healthy volunteers were recorded during wrist flexion-extension and rotation with sensitive uniaxial accelerometers placed at eight locations around the wrist. The acoustic data were bandpass filtered (150 Hz–20 kHz). The signal-to-noise ratio (SNR) was used to quantify the strength of the JAE signals in each recording. Then, nine audio features were extracted, and the intraclass correlation coefficient (ICC) (model 3,k), coefficients of variability (CVs), and Jensen–Shannon (JS) divergence were calculated to evaluate the interrater repeatability of the signals. We found that SNR ranged from 4.1 to 9.8 dB, intrasession and intersession ICC values ranged from 0.629 to 0.886, CVs ranged from 0.099 to 0.241, and JS divergence ranged from 0.18 to 0.20, demonstrating high JAE repeatability and signal strength at three locations. The volunteer sample size is not large enough to represent JAE analysis of a larger population, but this work will lay a foundation for future work in using wrist JAEs to aid in diagnosis and treatment tracking of musculoskeletal pathologies and injury in wearable systems.

scholarly journals Planetary bearing defect detection in a commercial helicopter main gearbox with vibration and acoustic emission

2018 ◽  
Vol 17 (5) ◽  
pp. 1192-1212 ◽  
Author(s):  
Faris Elasha ◽  
Matthew Greaves ◽  
David Mba
Keyword(s):  
Acoustic Emission ◽  
Signal To Noise Ratio ◽  
Acoustic Emissions ◽  
Research Programme ◽  
Vibration Signal ◽  
Operating Conditions ◽  
Broadband Wireless ◽  
Bearing Faults ◽  
Spectral Kurtosis ◽  
Signal Suppression

Helicopter gearboxes significantly differ from other transmission types and exhibit unique behaviours that reduce the effectiveness of traditional fault diagnostics methods. In addition, due to lack of redundancy, helicopter transmission failure can lead to catastrophic accidents. Bearing faults in helicopter gearboxes are difficult to discriminate due to the low signal-to-noise ratio in the presence of gear vibration. In addition, the vibration response from the planet gear bearings must be transmitted via a time-varying path through the ring gear to externally mounted accelerometers, which cause yet further bearing vibration signal suppression. This research programme has resulted in the successful proof of concept of a broadband wireless transmission sensor that incorporates power scavenging while operating within a helicopter gearbox. In addition, this article investigates the application of signal separation techniques in detection of bearing faults within the epicyclic module of a large helicopter (CS-29) main gearbox using vibration and acoustic emissions. It compares their effectiveness for various operating conditions. Three signal processing techniques, including an adaptive filter, spectral kurtosis and envelope analysis, were combined for this investigation. In addition, this research discusses the feasibility of using acoustic emission for helicopter gearbox monitoring.

scholarly journals Knee Acoustic Emissions as a Digital Biomarker of Disease Status in Juvenile Idiopathic Arthritis

2020 ◽  
Vol 2 ◽  
Author(s):  
Daniel C. Whittingslow ◽  
Jonathan Zia ◽  
Sevda Gharehbaghi ◽  
Talia Gergely ◽  
Lori A. Ponder ◽  
...  
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
Majority Vote ◽  
Acoustic Emissions ◽  
Disease Status ◽  
Clinical Work ◽  
Relevant Information ◽  
Classification Model ◽  
Flexion Extension ◽  
Joint Health

In this paper, we quantify the joint acoustic emissions (JAEs) from the knees of children with juvenile idiopathic arthritis (JIA) and support their use as a novel biomarker of the disease. JIA is the most common rheumatic disease of childhood; it has a highly variable presentation, and few reliable biomarkers which makes diagnosis and personalization of care difficult. The knee is the most commonly affected joint with hallmark synovitis and inflammation that can extend to damage the underlying cartilage and bone. During movement of the knee, internal friction creates JAEs that can be non-invasively measured. We hypothesize that these JAEs contain clinically relevant information that could be used for the diagnosis and personalization of treatment of JIA. In this study, we record and compare the JAEs from 25 patients with JIA−10 of whom were recorded a second time 3–6 months later—and 18 healthy age- and sex-matched controls. We compute signal features from each of those record cycles of flexion/extension and train a logistic regression classification model. The model classified each cycle as having JIA or being healthy with 84.4% accuracy using leave-one-subject-out cross validation (LOSO-CV). When assessing the full JAE recording of a subject (which contained at least 8 cycles of flexion/extension), a majority vote of the cycle labels accurately classified the subjects as having JIA or being healthy 100% of the time. Using the output probabilities of a JIA class as a basis for a joint health score and test it on the follow-up patient recordings. In all 10 of our 6-week follow-up recordings, the score accurately tracked with successful treatment of the condition. Our proposed JAE-based classification model of JIA presents a compelling case for incorporating this novel joint health assessment technique into the clinical work-up and monitoring of JIA.

scholarly journals Reliability of Vibroarthrography to Assess Knee Joint Sounds in Motion

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1998 ◽  
Author(s):  
Kristin Kalo ◽  
Daniel Niederer ◽  
Rainer Sus ◽  
Keywan Sohrabi ◽  
Volker Groß ◽  
...  
Keyword(s):  
Knee Joint ◽  
Intraclass Correlation ◽  
Acoustic Emissions ◽  
Correlation Coefficients ◽  
Mean Amplitude ◽  
Intraclass Correlation Coefficients ◽  
Washout Phase ◽  
Standing Up ◽  
Joint Health ◽  
Power Frequency

Knee acoustic emissions provide information about joint health and loading in motion. As the reproducibility of knee acoustic emissions by vibroarthrography is yet unknown, we evaluated the intrasession and interday reliability of knee joint sounds. In 19 volunteers (25.6 ± 2.0 years, 11 female), knee joint sounds were recorded by two acoustic sensors (16,000 Hz; medial tibial plateau, patella). All participants performed four sets standing up/sitting down (five repetitions each). For measuring intrasession reliability, we used a washout phase of 30 min between the first three sets, and for interday reliability we used a washout phase of one week between sets 3 and 4. The mean amplitude (dB) and median power frequency (Hz, MPF) were analyzed for each set. Intraclass correlation coefficients (ICCs (2,1)), standard errors of measurement (SEMs), and coefficients of variability (CVs) were calculated. The intrasession ICCs ranged from 0.85 to 0.95 (tibia) and from 0.73 to 0.87 (patella). The corresponding SEMs for the amplitude were ≤1.44 dB (tibia) and ≤2.38 dB (patella); for the MPF, SEMs were ≤13.78 Hz (tibia) and ≤14.47 Hz (patella). The intrasession CVs were ≤0.06 (tibia) and ≤0.07 (patella) (p < 0.05). The interday ICCs ranged from 0.24 to 0.33 (tibia) and from 0 to 0.82 (patella) for both the MPF and amplitude. The interday SEMs were ≤4.39 dB (tibia) and ≤6.85 dB (patella) for the amplitude and ≤35.39 Hz (tibia) and ≤15.64 Hz (patella) for the MPF. The CVs were ≤0.14 (tibia) and ≤0.08 (patella). Knee joint sounds were highly repeatable within a single session but yielded inconsistent results for the interday reliability.

scholarly journals At Home Photography-Based Method for Measuring Wrist Range of Motion

2017 ◽  
Vol 06 (04) ◽  
pp. 280-284 ◽  
Author(s):  
Samir Trehan ◽  
Schneider Rancy ◽  
Parker Johnsen ◽  
Howard Hillstrom ◽  
Steve Lee ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Digital Images ◽  
Intraclass Correlation ◽  
Office Visits ◽  
Wrist Flexion ◽  
Ulnar Deviation ◽  
Digital Photographs ◽  
Physician Contact ◽  
Flexion Extension ◽  
At Home

Purpose To determine the reliability of wrist range of motion (WROM) measurements based on digital photographs taken by patients at home compared with traditional measurements done in the office with a goniometer. Methods Sixty-nine postoperative patients were enrolled in this study at least 3 months postoperatively. Active and passive wrist flexion/extension and radial/ulnar deviation were recorded by one of the two attending surgeons with a 1-degree resolution goniometer at the last postoperative office visit. Patients were provided an illustrated instruction sheet detailing how to take digital photographic images at home in six wrist positions (active and passive flexion/extension, and radial/ulnar deviation). Wrist position was measured from digital images by both the attending surgeons in a randomized, blinded fashion on two separate occasions greater than 2 weeks apart using the same goniometer. Reliability analysis was performed using the intraclass correlation coefficient to assess agreement between clinical and photography-based goniometry, as well as intra- and interobserver agreement. Results Out of 69 enrolled patients, 30 (43%) patients sent digital images. Of the 180 digital photographs, only 9 (5%) were missing or deemed inadequate for WROM measurements. Agreement between clinical and photography-based measurements was “almost perfect” for passive wrist flexion/extension and “substantial” for active wrist flexion/extension and radial/ulnar deviation. Inter- and intraobserver agreement for the attending surgeons was “almost perfect” for all measurements. Discussion This study validates a photography-based goniometry protocol allowing accurate and reliable WROM measurements without direct physician contact. Passive WROM was more accurately measured from photographs than active WROM. This study builds on previous photography-based goniometry literature by validating a protocol in which patients or their families take and submit their own photographs. Clinical Relevance Patient-performed photography-based goniometry represents an alternative to traditional clinical goniometry that could enable longer-term follow-up, overcome travel-related impediments to office visits, improve convenience, and reduce costs for patients.

scholarly journals Design and Development of Continuous Passive Motion (CPM) for Fingers and Wrist Grounded-Exoskeleton Rehabilitation System

2021 ◽  
Vol 11 (2) ◽  
pp. 815
Author(s):  
Husam Almusawi ◽  
Géza Husi
Keyword(s):  
Experimental Testing ◽  
Hand Movement ◽  
Evaluation Process ◽  
Continuous Passive Motion ◽  
Wrist Flexion ◽  
Design And Development ◽  
Passive Motion ◽  
Assistive Robots ◽  
Flexion Extension ◽  
Design Characteristics

Impairments of fingers, wrist, and hand forearm result in significant hand movement deficiencies and daily task performance. Most of the existing rehabilitation assistive robots mainly focus on either the wrist training or fingers, and they are limiting the natural motion; many mechanical parts associated with the patient’s arms, heavy and expensive. This paper presented the design and development of a new, cost-efficient Finger and wrist rehabilitation mechatronics system (FWRMS) suitable for either hand right or left. The proposed machine aimed to present a solution to guide individuals with severe difficulties in their everyday routines for people suffering from a stroke or other motor diseases by actuating seven joints motions and providing them repeatable Continuous Passive Motion (CPM). FWRMS approach uses a combination of; grounded-exoskeleton structure to provide the desired displacement to the hand’s four fingers flexion/extension (F/E) driven by an indirect feed drive mechanism by adopting a leading screw and nut transmission; and an end-effector structure to provide angular velocity to the wrist flexion/ extension (F/E), wrist radial/ulnar deviation (R/U), and forearm supination/pronation (S/P) driven by a rotational motion mechanism. We employed a single dual-sided actuator to power both mechanisms. Additionally, this article presents the implementation of a portable embedded controller. Moreover, this paper addressed preliminary experimental testing and evaluation process. The conducted test results of the FWRMS robot achieved the required design characteristics and executed the motion needed for the continuous passive motion rehabilitation and provide stable trajectories guidance by following the natural range of motion (ROM) and a functional workspace of the targeted joints comfortably for all trainable movements by FWRMS.

scholarly journals DOING L2 SPEECH RESEARCH ONLINE: WHY AND HOW TO COLLECT ONLINE RATINGS DATA

2021 ◽  
pp. 1-24
Author(s):  
Charles L. Nagle ◽  
Ivana Rehman
Keyword(s):  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Control Measures ◽  
Mixed Effects Models ◽  
Amazon Mechanical Turk ◽  
Intraclass Correlation Coefficients ◽  
Online Ratings ◽  
Speech Research ◽  
Future Work ◽  
Local Laboratory

Abstract Listener-based ratings have become a prominent means of defining second language (L2) users’ global speaking ability. In most cases, local listeners are recruited to evaluate speech samples in person. However, in many teaching and research contexts, recruiting local listeners may not be possible or advisable. The goal of this study was to hone a reliable method of recruiting listeners to evaluate L2 speech samples online through Amazon Mechanical Turk (AMT) using a blocked rating design. Three groups of listeners were recruited: local laboratory raters and two AMT groups, one inclusive of the dialects to which L2 speakers had been exposed and another inclusive of a variety of dialects. Reliability was assessed using intraclass correlation coefficients, Rasch models, and mixed-effects models. Results indicate that online ratings can be highly reliable as long as appropriate quality control measures are adopted. The method and results can guide future work with online samples.

scholarly journals Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements

2019 ◽  
Vol 32 (23) ◽  
pp. 8087-8109 ◽  
Author(s):  
Mark D. Risser ◽  
Christopher J. Paciorek ◽  
Travis A. O’Brien ◽  
Michael F. Wehner ◽  
William D. Collins
Keyword(s):  
Extreme Precipitation ◽  
Seasonal Changes ◽  
Signal To Noise Ratio ◽  
Statistical Technique ◽  
In Situ Measurements ◽  
Absolute Sense ◽  
Underlying Causes ◽  
Changes Over Time ◽  
Future Work

Abstract The gridding of daily accumulated precipitation—especially extremes—from ground-based station observations is problematic due to the fractal nature of precipitation, and therefore estimates of long period return values and their changes based on such gridded daily datasets are generally underestimated. In this paper, we characterize high-resolution changes in observed extreme precipitation from 1950 to 2017 for the contiguous United States (CONUS) based on in situ measurements only. Our analysis utilizes spatial statistical methods that allow us to derive gridded estimates that do not smooth extreme daily measurements and are consistent with statistics from the original station data while increasing the resulting signal-to-noise ratio. Furthermore, we use a robust statistical technique to identify significant pointwise changes in the climatology of extreme precipitation while carefully controlling the rate of false positives. We present and discuss seasonal changes in the statistics of extreme precipitation: the largest and most spatially coherent pointwise changes are in fall (SON), with approximately 33% of CONUS exhibiting significant changes (in an absolute sense). Other seasons display very few meaningful pointwise changes (in either a relative or absolute sense), illustrating the difficulty in detecting pointwise changes in extreme precipitation based on in situ measurements. While our main result involves seasonal changes, we also present and discuss annual changes in the statistics of extreme precipitation. In this paper we only seek to detect changes over time and leave attribution of the underlying causes of these changes for future work.

Simultaneous Monitoring of Rolling-Element and Journal Bearings Using Analysis of Structure-Born Ultrasound Acoustic Emissions

2010 ◽  
Author(s):  
A. Albers ◽  
M. Dickerhof
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emissions ◽  
Piezoelectric Sensor ◽  
Journal Bearings ◽  
Rolling Element Bearings ◽  
Acoustic Emission Sensor ◽  
Outer Race ◽  
Rolling Element ◽  
Characteristic Values ◽  
Acoustic Emission Technology

The application of Acoustic Emission technology for monitoring rolling element or hydrodynamic plain bearings has been addressed by several authors in former times. Most of these investigations took place under idealized conditions, to allow the concentration on one single source of emission, typically recorded by means of a piezoelectric sensor. This can be achieved by either eliminating other sources in advance or taking measures to shield them out (e. g. by placing the acoustic emission sensor very close to the source of interest), so that in consequence only one source of structure-born sound is present in the signal. With a practical orientation this is often not possible. In point of fact, a multitude of potential sources of emission can be worth considering, unfortunately superimposing one another. The investigations reported in this paper are therefore focused on the simultaneous monitoring of both bearing types mentioned above. Only one piezoelectric acoustic emission sensor is utilized, which is placed rather far away from the monitored bearings. By derivation of characteristic values from the sensor signal, different simulated defects can be detected reliably: seeded defects in the inner and outer race of rolling element bearings as well as the occurrence of mixed friction in the sliding surface bearing due to interrupted lubricant inflow.

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