The Micro-Opto-Electro-Mechanical Systems (MOEMS) accelerometer is a new type of accelerometer that combines the merits of optical measurement and Micro-Electro-Mechanical Systems (MEMS) to enable ...high precision, small volume, and anti-electromagnetism disturbance measurement of acceleration, which makes it a promising candidate for inertial navigation and seismic monitoring. This paper proposes a modified micro-grating-based accelerometer and introduces a new design method to characterize the grating interferometer. A MEMS sensor chip with high sensitivity was designed and fabricated, and the processing circuit was modified. The micro-grating interference measurement system was modeled, and the response sensitivity was analyzed. The accelerometer was then built and benchmarked with a commercial seismometer in detail. Compared to the previous prototype in the experiment, the results indicate that the noise floor has an ultra-low self-noise of 15 ng/Hz
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Recognizing human physical activities from streaming smartphone sensor readings is essential for the successful realization of a smart environment. Physical activity recognition is one of the active ...research topics to provide users the adaptive services using smart devices. Existing physical activity recognition methods lack in providing fast and accurate recognition of activities. This paper proposes an approach to recognize physical activities using only2-axes of the smartphone accelerometer sensor. It also investigates the effectiveness and contribution of each axis of the accelerometer in the recognition of physical activities. To implement our approach, data of daily life activities are collected labeled using the accelerometer from 12 participants. Furthermore, three machine learning classifiers are implemented to train the model on the collected dataset and in predicting the activities. Our proposed approach provides more promising results compared to the existing techniques and presents a strong rationale behind the effectiveness and contribution of each axis of an accelerometer for activity recognition. To ensure the reliability of the model, we evaluate the proposed approach and observations on standard publicly available dataset WISDM also and provide a comparative analysis with state-of-the-art studies. The proposed approach achieved 93% weighted accuracy with Multilayer Perceptron (MLP) classifier, which is almost 13% higher than the existing methods.
Abstract Objective : To compare activity counts from the ActiGraph GT3X to those from the ActiGraph GT1M during treadmill walking/running. A secondary aim was to develop tri-axial vector magnitude ...(VM3) cut-points to classify physical activity (PA) intensity. Methods : Fifty participants wore the GT3X and the GT1M on the non-dominant hip and exercised at 4 treadmill speeds (4.8, 6.4, 9.7, and 12 km h−1 ). Vertical (VT) and antero-posterior (AP) activity counts (counts min−1 ) as well as the vector magnitudes of the two axes (VM2) from both monitors were tested for significant differences using two-way ANOVA's. Bland–Altman plots were used to assess agreement between activity counts from the GT3X and GT1M. Linear regression analysis between VM3 counts min−1 and oxygen consumption data was conducted to develop VM3 cut-points for moderate, hard and very hard PA. Results : There were no significant inter-monitor differences in VT activity counts at any speed. AP and VM2 activity counts from the GT1M were significantly higher ( p < 0.01) than those from the GT3X at 4.8, 9.7 and 12 km h−1 . High inter-monitor agreement was found for VT activity counts but not for AP and VM2 activity counts. VM3 cut-points for moderate, hard, and very hard PA intensities were 2690–6166, 6167–9642, >9642 counts min−1. Conclusion : Due to the lack of congruence between the AP and VM2 activity counts from the GT1M and the GT3X, comparisons of data obtained with these two monitors should be avoided when using more than just the VT axis. VM3 cut-points may be used to classify PA in future studies.
To evaluate the reliability and validity of the commercially available Fitbit Ultra (2012) accelerometer compared to polysomnography (PSG) and two different actigraphs in a pediatric sample.
All ...subjects wore the Fitbit Ultra while undergoing overnight clinical polysomnography in a sleep laboratory; a randomly selected subset of participants also wore either the Ambulatory Monitoring Inc. Motionlogger Sleep Watch (AMI) or Phillips-Respironics Mini-Mitter Spectrum (PRMM).
63 youth (32 females, 31 males), ages 3-17 years (mean 9.7 years, SD 4.6 years).
Both "Normal" and "Sensitive" sleep-recording Fitbit Ultra modes were examined. Outcome variables included total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). Primary analyses examined the differences between Fitbit Ultra and PSG using repeated-measures ANCOVA, with epoch-by-epoch comparisons between Fitbit Ultra and PSG used to determine sensitivity, specificity, and accuracy. Intra-device reliability, differences between Fitbit Ultra and actigraphy, and differences by both developmental age group and sleep disordered breathing (SDB) status were also examined.
Compared to PSG, the Normal Fitbit Ultra mode demonstrated good sensitivity (0.86) and accuracy (0.84), but poor specificity (0.52); conversely, the Sensitive Fitbit Ultra mode demonstrated adequate specificity (0.79), but inadequate sensitivity (0.70) and accuracy (0.71). Compared to PSG, the Fitbit Ultra significantly overestimated TST (41 min) and SE (8%) in Normal mode, and underestimated TST (105 min) and SE (21%) in Sensitive mode. Similar differences were found between Fitbit Ultra (both modes) and both brands of actigraphs.
Despite its low cost and ease of use for consumers, neither sleep-recording mode of the Fitbit Ultra accelerometer provided clinically comparable results to PSG. Further, pediatric sleep researchers and clinicians should be cautious about substituting these devices for validated actigraphs, with a significant risk of either overestimating or underestimating outcome data including total sleep time and sleep efficiency.
In this article, we review optical MEMS accelerometers with a particular focus on sensing techniques and interrogation methods. Optical accelerometers find use in various application domains ranging ...from microgravity to inertial navigation to vibration sensing. The performance of an accelerometer is quantified in terms of its range, bandwidth, sensitivity, and resolution. The combination of sensing technique and interrogation method determines the optical accelerometer's performance. This article presents a classification in terms of guided-wave and free-space based optical sensing techniques used in acceleration measurement and their review. In free-space based sensing techniques, light propagating in free-space interacts with the mechanical structure resulting in modification of light properties at the receiver. In guided-wave based sensing techniques, light interaction with the mechanical structure is confined to the waveguide. Also, the different interrogation methods used in optical MEMS accelerometers are reviewed. The interrogation methods are classified as based on intensity modulation or frequency modulation of the optical signal received from sensor. In intensity-modulation based interrogation, light intensity at output is the measurand and, the cost and complexity of this class of methods is lower. In frequency-modulation based interrogation, the frequency or phase of the optical signal at the output is the measurand. Further, a high-resolution optical MEMS accelerometer based on waveguide Bragg gratings is described. A combination of free-space based sensing and intensity-modulation based interrogation methods will be suitable for consumer-grade accelerometer applications. For high-resolution applications like tactical and navigation grades, a combination of guided-wave sensing and frequency-modulation based interrogation methods would be appropriate.
This paper reports an acceleration sensing method based on two weakly coupled resonators (WCRs) using the phenomenon of mode localization. When acceleration acts on the proof masses, differential ...electrostatic stiffness perturbations will be applied to the WCRs, leading to mode localization, and thus, mode shape changes. Therefore, acceleration can be sensed by measuring the amplitude ratio shift. The proposed mode localization with the differential perturbation method leads to a sensitivity enhancement of a factor of 2 than the common single perturbation method. The theoretical model of the sensitivity, bandwidth, and linearity of the accelerometer is established and verified. The measured relative shift in amplitude ratio (~312162 ppm/g) is 302 times higher than the shift in resonance frequency (~1035 ppm/g) within the measurement range of ±1 g. The measured resolution based on the amplitude ratio is 0.619 mg and the nonlinearity is ~3.5% in the open-loop measurement operation.
An integrated self‐powered dynamic displacement monitoring system by utilizing a novel triboelectric accelerometer for structural health monitoring is proposed and implemented in this study, which ...can show the dynamic displacement and transmit the alarming signal by accurately sensing the vibration acceleration. The fabricated triboelectric accelerometer based on the noncontact freestanding triboelectric nanogenerator consists of an outer transparent sleeve tube and an inner cylindrical inertial mass that is suspended by a highly stretchable silicone fiber. One pair of copper film electrodes is deposited by physical vapor deposition on nylon film and adhered on the inner wall of the outer tube, while a fluorinated ethylene propylene film with nanowire structures is adhered on the surface of the inner cylindrical inertial mass. The experimental results show that proposed triboelectric accelerometer can accurately sense the vibration acceleration with a high sensitivity of 0.391 V s2 m−1. In particular, the developed accelerometer has superior performance within the low‐frequency range. One of the most striking features is that the commercial accelerometer using piezoelectric material is strongly dominated by high‐order harmonics, which can cause confusion in computer data analysis. In contrast, the triboelectric accelerometer is only dominated by the base resonance mode.
Based on the noncontact freestanding triboelectric nanogenerator (TENG), a novel self‐powered accelerometer sensor with the sleeve‐tube structure for vibration detection is proposed and fabricated, which has more superior performance applying in lower vibration frequency compared with the traditional piezoelectric accelerometer. Moreover, an integrated self‐powered dynamic displacement monitoring system by utilizing a novel triboelectric accelerometer for structural health monitoring is developed.
The surface roughness of roads is an essential road characteristic. Due to the employed carrying platforms (which are often cars), existing measuring methods can only be used for motorable roads. ...Until now, there has been no effective method for measuring the surface roughness of un-motorable roads, such as pedestrian and bicycle lanes. This hinders many applications related to pedestrians, cyclists and wheelchair users. In recognizing these research gaps, this paper proposes a method for measuring the surface roughness of pedestrian and bicycle lanes based on Global Positioning System (GPS) and accelerometer sensors on bicycle-mounted smartphones. We focus on the International Roughness Index (IRI), as it is the most widely used index for measuring road surface roughness. Specifically, we analyzed a computing model of road surface roughness, derived its parameters with GPS and accelerometers on bicycle-mounted smartphones, and proposed an algorithm to recognize potholes/humps on roads. As a proof of concept, we implemented the proposed method in a mobile application. Three experiments were designed to evaluate the proposed method. The results of the experiments show that the IRI values measured by the proposed method were strongly and positively correlated with those measured by professional instruments. Meanwhile, the proposed algorithm was able to recognize the potholes/humps that the bicycle passed. The proposed method is useful for measuring the surface roughness of roads that are not accessible for professional instruments, such as pedestrian and cycle lanes. This work enables us to further study the feasibility of crowdsourcing road surface roughness with bicycle-mounted smartphones.
Differences in running gait between treadmill and overground running has been subject of study, while consistency of group differences between running surfaces has not been previously analysed. This ...study examined both the differences between running surfaces and the consistency of sex-based differences between surfaces in some spatiotemporal and kinematic variables measured by an inertial measurement unit fastened over the lumbar spine. Thirty-two (sixteen females) endurance runners firstly performed overground and then treadmill (1 % inclination) runs at speeds between 9–21 km∙h−1. Males showed lower flight time (FT) moderate effect size (ES) during treadmill running compared to overground, while females showed greater stride frequency (SF) (moderate ES), lower stride length (SL) (moderate ES), FT (moderate ES), and vertical (VT) trunk displacement (moderate ES), as well as greater medio-lateral (ML) trunk displacement (moderate ES). No differences in CT between surfaces were found (trivial to small). Furthermore, all the sex-differences were consistent between treadmill and overground running: Males showed lower SF (large and moderate ES, respectively), greater SL (large and moderate ES) and CT (moderate and large ES), lower FT (large ES), greater VT displacement (moderate to large ES), and lower ML displacement (moderate ES) than females. These results may be of interest to carefully transfer the running gait analyses between surfaces depending on sex.
Kidney stone disease (KSD), a significant health care problem within both developed and developing countries, has been associated with genetic risk factors. An association between physical activity ...and KSD risk also has been hypothesized, but studies have yielded inconsistent findings. This study investigated the association between the intensity of physical activity and the incidence of KSD accounting for genetic risk.
Prospective cohort study.
A total of 80,473 participants from the UK Biobank Study.
Physical activity levels, including total physical activity (TPA), moderate-to-vigorous intensity physical activity (MVPA), and light-intensity physical activity (LPA), were measured using accelerometers and quantified using a machine learning model. A polygenic risk score (PRS) for KSD was also constructed.
Individuals with KSD were identified using the International Classification of Diseases, Tenth Revision (ICD-10), and procedure codes for KSD surgery.
A Fine and Gray survival model was used to estimate the associations of incident KSD with TPA, MVPA, LPA, and PRS (as categorical variables). Restricted cubic splines were used to examine potential nonlinear associations within the fully adjusted models.
During an average follow-up of 6.19 years, 421 participants developed KSD. Participants in the highest quartiles of TPA, MVPA, and LPA had lower adjusted rates of KSD compared with those in the lowest quartiles: HR, 0.50 (95% CI, 0.44-0.56), 0.57 (95% CI, 0.51-0.64), and 0.66 (95% CI, 0.59-0.74), respectively. TPA, MVPA, and LPA were associated with a lower risk of KSD in participants with low and high genetic predisposition for KSD.
Selection bias as participants who provided accelerometry data may have been more adherent to health care.
Physical activity was negatively associated with the risk of KSD, regardless of the genetic risk. Future large studies are warranted to confirm and explain the mechanisms underlying these associations.
The association between the intensity of physical activity (PA) and the incidence of kidney stone disease (KSD) after accounting for genetic risk is unclear. We conducted a comprehensive prospective cohort study utilizing participants from the UK Biobank to assess the intensity of PA using accelerometers. Our study findings indicated that greater total PA, moderate-to-vigorous-intensity PA, and light-intensity PA were each associated with a lower risk of KSD irrespective of an individual’s genetic risk. Our study informs the understanding of risk factors for KSD.
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