A method to estimate relative orientations of body segments during movement using accelerometry

Quantitative assessment of human body movements includes the analysis of joint orientations. We propose a new method to estimate relative orientation between body segments using a single 3D accelerometer per segment

Motion Capture: From Radio Signals to Inertial Signals

The study of the motion of individuals allows to gather relevant information on a person status, to be used in several fields (e.g., medical, sport, and entertainment). Over the past decade, the research activity in motion capture has benefited from the progress of portable and mobile sensors, paving the way toward the use of motion capture techniques in mHealth applications (e.g., remote monitoring of patients, and telerehabilitation). Indeed, even if the optical motion capture, which typically relies on a set of fixed cameras and body-worn reflecting markers, is generally perceived as the standard reference approach, other motion capture techniques, such as radio and inertial, are attracting an increasing attention because of their suitability in remote mHealth applications. Moreover, several hybrid approaches have been studied and proposed in order to overcome the limitations of component technologies considered independently. In this chapter, we present an overview of possible integration strategies between radio and inertial motion capture techniques. We start by investigating a radio-based approach, based on the fingerprinting radio localization technique. Then, the previous approach is improved by integrating inertial measurements: namely, accelerometers are used to provide an estimate of the nodes’ pitches. Finally, the radio signals are abandoned in favor of only inertial measurements (obtained through accelerometers, gyroscopes, and magnetometers). The advantages and limitations of all approaches are discussed in a comparative way, characterizing the similarities and differences between the various approaches

Susceptibility to chronic mucus hypersecretion, a genome wide association study

Background: Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25x10-6, OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3x10 -9) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH

Measuring orientation of human body segments using miniature gyroscopes and accelerometers

In the medical field, there is a need for small ambulatory sensor systems for measuring the kinematics of body segments. Current methods for ambulatory measurement of body orientation have limited accuracy when the body moves. The aim of the paper was to develop and validate a method for accurate measurement of the orientation of human body segments using an inertial measurement unit (IMU). An IMU containing three single-axis accelerometers and three single-axis micromachined gyroscopes was assembled in a rectangular box, sized 20×20×30 mm. The presented orientation estimation algorithm continuously corrected orientation estimates obtained by mathematical integration of the 3D angular velocity measured using the gyroscopes. The correction was performed using an inclination estimate continuously obtained using the signal of the 3D accelerometer. This reduces the integration drift that originates from errors in the angular velocity signal. In addition, the gyroscope offset was continuously recalibrated. The method was realised using a Kalman filter that took into account the spectra of the signals involved as well as a fluctuating gyroscope offset. The method was tested for movements of the pelvis, trunk and forearm. Although the problem of integration drift around the global vertical continuously increased in the order of 0.5°s −1, the inclination estimate was accurate within 3° RMS. It was shown that the gyroscope offset could be estimated continuously during a trial. Using an initial offset error of 1 rads −1, after 2 min the offset error was roughly 5% of the original offset error. Using the Kalman filter described, an accurate and robust system for ambulatory motion recording can be realised

Ambulatory measurement of arm orientation

In order to evaluate the impact of neuromuscular disorders affecting the upper extremities, the functional use of the arm need to be evaluated during daily activities. A system suitable for measuring arm kinematics should be ambulatory and not interfere with activities of daily living. A measurement system based on miniature accelerometers and gyroscopes is adequate because the sensors are small and do not suffer from line of sight problems. A disadvantage of such sensors is the cumulative drift around the vertical and the problems with aligning the sensor with the segment.\ud \ud A method that uses constraints in the elbow to measure the orientation of the lower arm with respect to the upper arm is described. This requires a calibration method to determine the exact orientation of each of the sensors with respect to the segment. Some preliminary measurements were analyzed and they indicated a strong reduction in orientation error around the vertical. It seemed that the accuracy of the method is limited by the accuracy of the sensor to segment calibration

Estimating orientation with gyroscopes and accelerometers

Many systems for recording human movement need some reference from beacons near the subject, such as video cameras. Our goal is to measure human kinematics with sensors that are placed on the segments of interest. This way, experiments in which human movement is recorded are not restricted to a lab.\ud Our inertial sensor-unit consists of a little box with three miniature gyroscopes (Murata ENC05E) and three linear accelerometers (AD xl05) that measure 3D angular velocity and linear acceleration, respectively. Both the gyroscope and accelerometer signals contain information about the orientation of the sensor. The sensor orientation can be obtained by integration of the angular velocity signals obtained from the gyroscopes [1]. This operation introduces drift in the estimated orientation.\ud Accelerometers do not only measure the acceleration of the sensor, but also the gravitational vector. This gravitational component not only has a bigger magnitude for many human movements but also always points downwards. This knowledge can be used to make an estimation of the tilt. The tilt is the angle between the sensor axes and the vertical. This tilt estimation is not very precise but does not suffer from drift.\ud The abstract describes a way to fuse both sensors (gyroscopes and accelerometers) to obtain an estimate of the orientation that is both accurate and is limited in integration drift

Artificial intelligence used for the interpretation of combined spectral data *1 : Part II. PEGASUS: a PROLOG program for the generation of acyclic molecular structures

A computer program, PEGASUS (PROLOG-based EXSPEC Generator for Acyclic StrUctureS), has been developed which can be used to generate exhaustively and non-redundantly all possible acyclic isomers that satisfy a given molecular weight or formula PEGASUS was written in PROLOG and implemented on an inexpensive personal computer (Apple Macintosh Plus). The program is described and the scope for its application is surveyed