Accelerometer Output Research Articles

Activity monitoring reflects cardiovascular and metabolic variations in COPD patients across GOLD stages II to IV

We investigated whether activity monitoring reliably reflects variations in oxygen transport and utilization during walking in COPD patients. Forty-two patients (14 in each GOLD stage II, III and IV) performed an incremental treadmill protocol to the limit of tolerance. Breath-by-breath gas exchange, central hemodynamic variables and activity monitoring were simultaneously recorded. Physiological variables and accelerometer outputs rose linearly with walking speeds. Strong correlations (r[interquartile range, IQR]) were found between treadmill walking intensity (WI: range 0.8–2.0ms−2) and oxygen consumption (0.95 [IQR 0.87–0.97]), (range 7.6–15.5mlkg−1min−1); minute ventilation (0.95 [IQR 0.86–0.98]), (range 20–37lmin−1); cardiac output (0.89 [IQR 0.73–0.94]), (range 6.8–11.5lmin−1) and arteriovenous oxygen concentration difference (0.84 [IQR 0.76–0.90]), (range 7.7–12.1ml O2100ml−1). Correlations between WI and gas exchange or central hemodynamic parameters were not different across GOLD stages. In conclusion, central hemodynamic, respiratory and muscle metabolic variations during incremental treadmill exercise are tightly associated to changes in walking intensity as recorded by accelerometry across GOLD stages II to IV. Interestingly, the magnitude of these associations is not different across GOLD stages.

Research on Temperature Compensation Method of Quartz Flexible Accelerometer

In view of the problem of quartz flexible accelerometer output which is influenced by temperature, through the 12 gravity rolling experiment method, the temperature model of the partial value and the scaling factor of the accelerometer can be established in the designed experimental platform. Thus, the temperature compensation model of the accelerometer can be determined. It basically eliminates the output error of the accelerometer which varies with the temperature and improves the output precision of the accelerometer.

Tele-accelerometry as a novel technique for assessing functional status in patients with heart failure: Feasibility, reliability and patient safety

BackgroundThe six-minute walk test (6MWT) is an established measure of functional exercise capacity associated with clinical prognosis in Chronic Heart Failure (CHF). The aim of this study is to evaluate the employment of tele-accelerometry for the remote assessment of 6MWT in CHF. Methods155 patients were subjected to tele-accelerometry in form of monthly 6MWTs in their home surroundings. Accelerometer output included steps/6min and walking speed. Data was directly transferred via mobile network to the Telemedicine Centre subsequent to test completion. 6MWT distance was measured by hand wheel and steps were counted with a digital hand-counter at baseline (Test 1) and at 12months follow-up (Test 2). ResultsAccelerometer accuracy was within the 99th percentile. There was a significant correlation between step count, walking speed and measured 6MWT distance (Test 1: steps: r=0.80, P<0.001; Test 2: steps: r=0.90, P<0.001 and Walking Speed Test 1: r=0.80, P<0.001; Walking Speed Test 2: r=0.86, P<0.001). The reproducibility of tele-accelerometry was within 95% margin for all performance parameters, which showed stronger associations to quality of life questionnaire (Short Form - 36) Physical Component Score (PCS) than New York Heart Association (NYHA) functional class. ConclusionTele-accelerometry is feasible in patients with CHF and output parameters are indicative of exercise capacity. The benefit of this approach lies in its simplicity under every day circumstances by enabling routine performance testing to assess patients' functional status.

Research on Accelerometer Output Error for Rotational Inertial Navigation System

In order to restrain the accelerometer output error in rotational inertial navigation systems (INS), the imbalance torque of inertial measurement unit (IMU) and the magnetic field of motor were analyzed based on engineering application. The cause of imbalance torque and its influence mechanism were explained. Method taking plumbum mass to balance the IMU was proposed. The influence mechanism of motors magnetic field on accelerometer output was discussed. Method taking differential signal to communicate was devised. The compared results show the accelerometer output error is decreased effectively after taking these two methods. There is lower noise and no slow drift or hop count in accelerometer output.

Attitude Angle Measurement Method Based on the Three-Dimensional Accelerometer

On the basis of a study of measuring inclination angle with a two-dimensional accelerometer, a principle method using a three-dimensional accelerometer to measure attitude angle is analysed on the condition of micro-rotating. The method can reduce random systematic errors caused by uniaxial or biaxial output of the two-dimensional accelerometer. It can simultaneously measure both inclination angle and roll angle. So hardware selection, hardware circuit design and experiments are done: simulate the roll and tilt movement of the special objects and compare the solver results with the actual results. The principle method achieves preferable results, and provides a theoretical support for attitude determination of a particular industry as well.

SAT0246 Physical Activity in Patients with Ankylosing Spondylitis Compared to Healthy Controls.

BackgroundAnkylosing spondylitis (AS) is a rheumatic inflammatory disease that mainly affects the axial skeleton. Important symptoms comprise pain, (morning) stiffness, fatigue, reduced mobility and limitations in the physical function. Likely...

Support vector machines classifiers of physical activities in preschoolers

The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3–5 years old were asked to participate in a supervised protocol of physical activities while wearing a triaxial accelerometer. Accelerometer counts, steps, and position were obtained from the device. We applied K-means clustering to determine the number of natural groupings presented by the data. We used MLR and SVM to classify the six activity types. Using direct observation as the criterion method, the 10-fold cross-validation (CV) error rate was used to compare MLR and SVM classifiers, with and without sleep. Altogether, 58 classification models based on combinations of the accelerometer output variables were developed. In general, the SVM classifiers have a smaller 10-fold CV error rate than their MLR counterparts. Including sleep, a SVM classifier provided the best performance with a 10-fold CV error rate of 24.70%. Without sleep, a SVM classifier-based triaxial accelerometer counts, vector magnitude, steps, position, and 1- and 2-min lag and lead values achieved a 10-fold CV error rate of 20.16% and an overall classification error rate of 15.56%. SVM supersedes the classical classifier MLR in categorizing physical activities in preschool-aged children. Using accelerometer data, SVM can be used to correctly classify physical activities typical of preschool-aged children with an acceptable classification error rate.

CAN Network Based Longitudinal Velocity Measurement Using Accelerometer and GPS Receiver for Automobiles

A design of Controller Area Network (CAN) based longitudinal velocity measurement system using MEMS accelerometer and GPS receiver is presented. CAN is a serial communication protocol which efficiently supports distributed control system with high level of security. The system consists of a master node and a slave node built around LPC1768 and LPC2129 microcontrollers respectively. The master and slave nodes are linked with CAN bus. The slave node gets velocity data from GPS receiver and transfers to the master node. The master node samples the accelerometer output, and saves the sampled data and the velocity data received from the slave node on a microSD card. A LabVIEW program has been developed to study the measured parameters in offline by applying a Kalman filter and computing the estimate of longitudinal velocity. Typical measurements with the present system in a standard driving maneuvers and computation of estimate of longitudinal velocity using the LabVIEW program are presented. The measurement system produces comparable results with the conventional meter.

Physical activity characteristics and depressive symptoms in older Latino adults

BackgroundPhysical activity (PA) has been consistently associated with fewer depressive symptoms in observational and intervention studies. Emphasis on leisure-time PA, reliance on self report measures of PA, and lack of inclusion of racial/ethnic minority populations have contributed to uncertainty regarding the minimal and optimal dose (minutes/day), intensity (i.e., light, moderate, or vigorous), bout duration (i.e., incidental vs. 10-min bouts), and domain (i.e., leisure-time, occupational, and household) of PA for reducing and preventing depressive symptoms across diverse populations. PurposeTo investigate the relationship between PA characteristics (i.e., dose, intensity, bout duration, and domain) and depressive symptoms in older Latinos using both objective and subjective measures of PA. MethodsOlder Latinos (n = 174) completed questionnaires and wore accelerometers for seven days. Accelerometer output provided daily minutes of sedentary, light, and moderate-vigorous PA (MVPA) overall and in 10-min bouts. The Community Healthy Activity Model Program for Seniors (CHAMPS) questionnaire provided daily minutes of leisure-time PA, household PA, and sedentary activities. Hierarchical linear regression analysis was used to predict Center for Epidemiological Studies Depression Scale (CES-D) score. ResultsAfter controlling for established correlates of depressive symptoms (i.e., demographics, acculturation, and health characteristics), MVPA in ≥10-min bouts independently predicted fewer depressive symptoms (β = −.231, ΔR2 = .052, p ≤ .01) and household PA greater depressive symptoms (β = .263, ΔR2 = .056, p ≤ .001). ConclusionsResults suggest that PA intensity, bout duration, and domain influence the strength and direction of the relationship between PA and depressive symptoms in older Latino adults.

Identification Method of Sensor Directions and Sensitivities in Multi-Axis Accelerometer (Actual Measurement of Direction Tensor and Sensitivity Tensor)

An accelerometer generally has direction gaps between the package and the actual sensors. Conventional accelerometer calibration methods, e.g., ISO standard, do not consider this direction gap. This study proposes a new calibration method. The method uses a new examination system with a parallel linkage exciter mechanism. The exciter rotates a target accelerometer in a uniform circular motion, and the posture of the accelerometer is kept constant against external coordinates. The required torque for the rotation is small and constant because the rotation components are balanced with counterweights. Therefore, the exciter applies a stable sine wave acceleration to the accelerometer. This method contributes not only to the accuracy of input acceleration but also to the removal of offset noise. In addition, the input acceleration is calculated only by one differential computation, whereas an ordinary mechanism requires a second order differential. From the accelerometer output, a plane including the actual sensor direction is detected by the sine curve profile. The direction of the actual sensor is the line of intersection of two measured planes. For a 3-axis accelerometer, measurement 2 times is enough to determine all actual sensor directions and sensitivities with this method (measurement one time is enough for a 2-axis accelerometer). Actual sensor directions and sensitivities are experimentally examined. The result is consistent with the data sheet of the test accelerometer.11. This paper is the full translation from the transactions of JSME, Series C, Vol.78, No.786, pp. 499-507, 2012.

가속도계와 기압계를 이용한 경사면에서의 보행 거리 추정

Using a relationship between step length and accelerometer output, step length can be estimated. In this paper, we propose a new step length estimation algorithm, which can be used both for the plane and the slope by compensating the slope angle. The slope angle is estimated using a barometer and the slope angle is compensated by observing how the slope affects the step length estimation. The proposed algorithm is verified using five adult man walking data, where the average length error is about 3% regardless of the slope.

METs and Accelerometry of Walking in Older Adults

This study aimed to measure the metabolic cost (METs) of walking activities in older adults, to examine the relationship between accelerometer output and METs across walking activities, and to compare measured MET values in older adults with the MET values in the compendium. Twenty older adults (mean age = 75, range = 60-90 yr) completed eight walking activities (five treadmill based, three free living) for 6 min each. Oxygen consumption (V˙O2) and resting metabolic rate (RMR) were measured using a portable metabolic system, and motion was recorded using a waist-mounted ActiGraph accelerometer (GT3X; ActiGraph, Pensicola, FL). Energy expenditure across activities was defined as kilocalories per minute and measured as METs (V˙O2 / RMR) and standard METs (V˙O2 / 3.5 mL·kg-1·min-1). Mixed modeling was used to assess differences in counts per minute and kilocalories per minute by weight status, sex, comorbidity status, and functional status. Linear regression analysis was applied to develop a prediction equation for kilocalories per minute. Energy costs of walking were subsequently compared with METs in the compendium of physical activities. Average measured RMR was 2.6 mL·kg-1·min-1, 31.6% less than the standard RMR of 3.5 mL·kg-1·min-1. On average, standard METs were 71% lower than the measured METs across all walking activities. Measured MET levels differed from previously reported values in the literature and values listed in the compendium, resulting in misclassification of activity intensities for 60% of the walking conditions. Average counts for the walking activities ranged from 809 (treadmill = 1.5 mph) to 4593 counts per minute (treadmill = 3.5 mph). Previous regression equations consistently overestimate all activities compared with the measured energy cost in this sample of older adults. This study identifies the need for equations and cut points specific to older adults.

Performance Evaluation of MMA7260QT and ADXL345 on Self Balancing Robot

A self balancing robot (SBR) controller needs to detect platform inclination. For this purpose, an accelerometer is used. From various types of accelerometer, we can divide into digital and analog ones. The problem is how to select the right type for the SBR. This paper evaluates the performance of the ADXL345, 3-axis digital output accelerometer and the MMA7260QT, 3-axis analog output accelerometer. The Arduino is used to read data from the sensor and send it to PC for plotting. Both sensors use the lowest sensitivity. The sensors are evaluated with three criteria, i.e. stationary, dynamical response and collaborating with ITG3200 3-axis gyroscope for Kalman filter fusion. For stationary criterion, the ADXL345 is better than the other sensor for all stationary position. For dynamical response, both sensors suffer from the noise due to acceleration of the platform. The sensors do not only sense the gravity but also the acceleration of the platform when it is moved. But the noise level for the ADXL345 is lower than the other. Using Kalman filter makes both sensors show good performance for a SBR application. If three criteria are combined with hardware aspect, then the authors recommend using the ADXL345. Besides, it has several useful features to handle abrupt acceleration.

Non-iterative calibration for accelerometers with three non-orthogonal axes, reliable measurement setups and simple supplementary equipment

The input–output relationship of an accelerometer depends on parameters that are sensitive to temperature and air humidity. High accuracy field measurements therefore require simple in-field estimation of these parameters. We present an extension of a simple non-iterative six-parameter calibration method for triaxial accelerometers with orthogonal input axes to a nine-parameter method that also handles non-orthogonal axes and cross-axis interference. The method is based on measurements of the Earth gravity with the accelerometer placed at rest in at least nine different orientations. The main difference from previous work is that we derive necessary and sufficient conditions on the accelerometer output that tell whether calibration is possible, model the joint effect of non-orthogonal axes and cross-axis interference, provide closed form expressions for computing the parameter values and do a closer investigation and comparison of different ways to choose the accelerometer orientations for successful calibration. We compare two different setups, one called A90 − 450, which is based on 90° and 45° rotations of the accelerometer and one called Amax sep0 that has the maximized smallest angle between any two of the orientations. For the A90 − 450 setup we have constructed simple test equipment for quick positioning of the accelerometer. For the Amax sep0 setup, similar equipment is more complicated to construct, but equally simple to use. In Monte Carlo simulations with accelerometer orientations deviating at most D degrees from the desired A90 − 450 or Amax sep0 setup, equipment with D < 10° was enough for reliable calibration. For noise standard deviation typical for field measurements and for D up to 18°, our simulations showed slightly smaller errors for the Amax sep0 than for the A90 − 450 setup. The measurement errors after nine-parameter calibration were about 100 times smaller than those for six-parameter calibration both for the Amax sep0 setup and, as long as D ⩽ 13°, for the A90 − 450 setup. For the A90 − 450 setup, however, we found that combinations of large noise levels and/or large D can make six-parameter calibration the better choice.

Daily physical activity assessment with accelerometers: new insights and validation studies

The field of application of accelerometry is diverse and ever expanding. Because by definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) method as gold standard to assess total energy expenditure over longer periods of time is the method of choice to validate accelerometers in their ability to assess daily physical activities. The aim of this paper was to provide a systematic overview of all recent (2007-2011) accelerometer validation studies using DLW as the reference. The PubMed Central database was searched using the following keywords: doubly or double labelled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. Limits were set to include articles from 2007 to 2011, as earlier publications were covered in a previous review. In total, 38 articles were identified, of which 25 were selected to contain sufficient new data. Eighteen different accelerometers were validated. There was a large variability in accelerometer output and their validity to assess daily physical activity. Activity type recognition has great potential to improve the assessment of physical activity-related health outcomes. So far, there is little evidence that adding other physiological measures such as heart rate significantly improves the estimation of energy expenditure.

Effective accelerometer test beds for output enhancement of an inertial navigation system

This paper is submitted upon a research to enhance the output of an accelerometer widely used in inertial navigation units. In our study we introduce relatively simple and effective test beds to collect accurate and diverse reference data. We also carried out calibration runs with a highly accurate electromechanical shaking table. The proposed test beds compare well with sophisticated counterparts. The collected data is used to train artificial neural networks (ANNs) which would improve the accelerometer outputs by estimating the reference data from the actual sensor outputs. The ANN performance is compared with classic low pass filtering methods to provide a relative performance criterion. In this paper we focus on test beds rather than to give the details of the whole study. The test beds introduced in this research can be used for acquiring reference data for implementation of other different filter methods as well.

Quasi-Real Time Estimation of Angular Kinematics Using Single-Axis Accelerometers

In human movement modeling, the problem of multi-link kinematics estimation by means of inertial measurement units has been investigated by several authors through efficient sensor fusion algorithms. In this perspective a single inertial measurement unit per link is required. This set-up is not cost-effective compared with a solution in which a single-axis accelerometer per link is used. In this paper, a novel fast technique is presented for the estimation of the sway angle in a multi-link chain by using a single-axis accelerometer per segment and by setting the boundary conditions through an ad hoc algorithm. The technique, based on the windowing of the accelerometer output, was firstly tested on a mechanical arm equipped with a single-axis accelerometer and a reference encoder. The technique is then tested on a subject performing a squat task for the knee flexion-extension angle evaluation by using two single-axis accelerometers placed on the thigh and shank segments, respectively. A stereo-photogrammetric system was used for validation. RMSEs (mean ± std) are 0.40 ± 0.02° (mean peak-to-peak range of 147.2 ± 4.9°) for the mechanical inverted pendulum and 1.01 ± 0.11° (mean peak-to-peak range of 59.29 ± 2.02°) for the knee flexion-extension angle. Results obtained in terms of RMSE were successfully compared with an Extended Kalman Filter applied to an inertial measurement unit. These results suggest the usability of the proposed algorithm in several fields, from automatic control to biomechanics, and open new opportunities to increase the accuracy of the existing tools for orientation evaluation.

A Validation Test of Measurement Method of Lower Limb Angles Based on Kalman Filter on Different Type of Inertial Sensors

Lower limb joint angle measurement method based on Kalman filter was tested using commercially available inertial sensors in our previous study for a rehabilitation use. Although the angle measurement method was effective, measurement with the wireless sensors were affected by wireless communication environment. Wired and wireless inertial sensor systems were developed in our laboratory for solving the wireless communication problem. This paper aimed to examine the 2 developed sensors, since those were different from the previously used sensors in data communication system or resolution in measurement. The 2 developed sensors and 2 commercially available sensors were evaluated in measurements of inclination and joint angles of a rigid body model comparing to the results of an optical motion measurement system. The angles were measured by correcting the angles calculated from outputs of gyroscopes based on a Kalman filter using outputs of accelerometers. All of the sensors showed small RMS errors under the static and dynamic conditions. The results suggested that various inertial sensors could measure inclination and joint angles stably if angles are calculated by using the Kalman filtering based method. It would be possible to replace sensors with inexpensive or latest commercially available sensors.

J164012 多機能センサによる膝関節運動の測定方法([J164-01]医療・健康・福祉のためのセンシングおよびロボティクス(1))

This paper presents a method of measuring knee joint motion for clinical diagnostic procedures. MRI or optical tracking methods are examples of existing methods to quantify diagnostic procedures for assessing knee joint ligament injury. However, these methods require a large amount of space and are quite expensive. An alternative method is to use multifunctional sensors which contain tri-axial accelerometers and gyroscopes. Accelerometers can measure the tilt angle against the gravity vector and estimate the translational acceleration. Gyroscopes can measure the angle of rotary motion. An angle obtained by a gyroscope is normally influenced by noise; causing a bias in angle. This work presents a system using a Kalman filter to remove the bias angle obtained by the gyroscope. Experiments that measure three rotary motions and a translational motion of the knee joint were conducted. Sensors are mounted on the Tibia and Femur bone of a knee joint model. It was found that the bias of the gyroscope's output was minimized in all three rotary motions by applying the proposed system. In addition, translational distance was calculated by integrating the accelerometer's output. However, distance obtained by acceleration is significantly influenced by noises due to double integration. A method to process the acceleration data and obtain translational distance is also proposed.

Accelerometry as a measure of walking behavior in multiple sclerosis.

Accelerometry has been identified as a possible ecologically valid and objective approach for measuring community ambulation in multiple sclerosis (MS). This study provides a validation of accelerometer output based on associations with Expanded Disability Status Scale (EDSS), Patient Determined Disease Steps (PDDS) Scale, and Multiple Sclerosis Walking Scale-12 (MSWS-12) scores, timed 25-foot walk (T25FW) and 6-min walk (6MW) performance, oxygen cost (O(2) cost) of walking, and spatial and temporal parameters of gait. 256 persons with MS completed the PDDS and MSWS-12, underwent an examination for the generation of an EDSS score, undertook two T25FW tests and a 6MW while wearing a portable metabolic unit for measuring the O(2) cost of walking, completed two trials of comfortable walking on a GAITRite electronic walkway for measuring spatial and temporal parameters of gait, and then wore an Actigraph accelerometer during the waking hours of a 7-day period. The accelerometer output was significantly correlated with EDSS (ρ = -0.522), PDDS (ρ = -0.551), and MSWS-12 (ρ = -0.617) scores, T25FW (ρ = -0.595) and 6MW (ρ = 0.630) performance, and O(2) cost of walking (ρ = -0.457). Regarding gait parameters, the accelerometer output was significantly correlated with velocity (ρ = 0.420), cadence (ρ = 0.349), step time (ρ = -0.353), step length (ρ = 0.395), double support (ρ = -0.424), and single support (ρ = 0.400). We provide comprehensive evidence from a large sample of persons with MS that further supports accelerometry as a measure of walking behavior.