How useful is satellite positioning system (GPS) to track gait parameters? A review.

Over the last century, numerous techniques have been developed to analyze the movement of humans while walking and running. The combined use of kinematics and kinetics methods, mainly based on high speed video analysis and forceplate, have permitted a comprehensive description of locomotion process in terms of energetics and biomechanics. While the different phases of a single gait cycle are well understood, there is an increasing interest to know how the neuro-motor system controls gait form stride to stride. Indeed, it was observed that neurodegenerative diseases and aging could impact gait stability and gait parameters steadiness. From both clinical and fundamental research perspectives, there is therefore a need to develop techniques to accurately track gait parameters stride-by-stride over a long period with minimal constraints to patients. In this context, high accuracy satellite positioning can provide an alternative tool to monitor outdoor walking. Indeed, the high-end GPS receivers provide centimeter accuracy positioning with 5-20 Hz sampling rate: this allows the stride-by-stride assessment of a number of basic gait parameters--such as walking speed, step length and step frequency--that can be tracked over several thousand consecutive strides in free-living conditions. Furthermore, long-range correlations and fractal-like pattern was observed in those time series. As compared to other classical methods, GPS seems a promising technology in the field of gait variability analysis. However, relative high complexity and expensiveness--combined with a usability which requires further improvement--remain obstacles to the full development of the GPS technology in human applications.

High-precision satellite positioning system as a new tool to study the biomechanics of human locomotion.

New Global Positioning System (GPS) receivers allow now to measure a location on earth at high frequency (5Hz) with a centimetric precision using phase differential positioning method. We studied whether such technique was accurate enough to retrieve basic parameters of human locomotion. Eight subjects walked on an athletics track at four different imposed step frequencies (70-130steps/min) plus a run at free pace. Differential carrier phase localization between a fixed base station and the mobile antenna mounted on the walking person was calculated. In parallel, a triaxial accelerometer, attached to the low back, recorded body accelerations. The different parameters were averaged for 150 consecutive steps of each run for each subject (total of 6000 steps analyzed). We observed a perfect correlation between average step duration measured by accelerometer and by GPS (r=0.9998, N=40). Two important parameters for the calculation of the external work of walking were also analyzed, namely the vertical lift of the trunk and the velocity variation per step. For an average walking speed of 4.0km/h, average vertical lift and velocity variation were, respectively, 4.8cm and 0.60km/h. The average intra-individual step-to-step variability at a constant speed, which includes GPS errors and the biological gait style variation, were found to be 24. 5% (coefficient of variation) for vertical lift and 44.5% for velocity variation. It is concluded that GPS technique can provide useful biomechanical parameters for the analysis of an unlimited number of strides in an unconstrained free-living environment.

Improving Satellite Image Based Forest Inventory by Using A Priori Site Quality Information

Summary

Measurement of the mechanical power of walking by satellite positioning system (GPS).

PURPOSE: This descriptive article illustrates the application of Global Positioning System (GPS) professional receivers in the field of locomotion studies. The technological challenge was to assess the external mechanical work in outdoor walking. METHODS: Five subjects walked five times during 5 min on an athletic track at different imposed stride frequency (from 70-130 steps x min(-1)). A differential GPS system (carrier phase analysis) measured the variation of the position of the trunk at 5 Hz. A portable indirect calorimeter recorded breath-by-breath energy expenditure. RESULTS: For a walking speed of 1.05 +/- 0.11 m x s(-1), the vertical lift of the trunk (43 +/- 14 mm) induced a power of 46.0 +/- 20.4 W. The average speed variation per step (0.15 +/- 0.03 m x s(-1)) produced a kinetic power of 16.9 +/- 7.2 W. As compared with commonly admitted values, the energy exchange (recovery) between the two energy components was low (39.1 +/- 10.0%), which induced an overestimated mechanical power (38.9 +/- 18.3 W or 0.60 W x kg(-1) body mass) and a high net mechanical efficiency (26.9 +/- 5.8%). CONCLUSION: We assumed that the cause of the overestimation was an unwanted oscillation of the GPS antenna. It is concluded that GPS (in phase mode) is now able to record small body movements during human locomotion, and constitutes a promising tool for gait analysis of outdoor unrestrained walking. However, the design of the receiver and the antenna must be adapted to human experiments and a thorough validation study remains to be conducted.

Improvement of walking speed prediction by accelerometry and altimetry, validated by satellite positioning.

Activity monitors based on accelerometry are used to predict the speed and energy cost of walking at 0% slope, but not at other inclinations. Parallel measurements of body accelerations and altitude variation were studied to determine whether walking speed prediction could be improved. Fourteen subjects walked twice along a 1.3 km circuit with substantial slope variations (-17% to +17%). The parameters recorded were body acceleration using a uni-axial accelerometer, altitude variation using differential barometry, and walking speed using satellite positioning (DGPS). Linear regressions were calculated between acceleration and walking speed, and between acceleration/altitude and walking speed. These predictive models, calculated using the data from the first circuit run, were used to predict speed during the second circuit. Finally the predicted velocity was compared with the measured one. The result was that acceleration alone failed to predict speed (mean r = 0.4). Adding altitude variation improved the prediction (mean r = 0.7). With regard to the altitude/acceleration-speed relationship, substantial inter-individual variation was found. It is concluded that accelerometry, combined with altitude measurement, can assess position variations of humans provided inter-individual variation is taken into account. It is also confirmed that DGPS can be used for outdoor walking speed measurements, opening up new perspectives in the field of biomechanics.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Yhteisö-tv palvelukonseptina, case: Finnish Satellite Television Oy

Menestyäkseen nykymaailmassa ihmiset ovat turvautuneet toisiinsa muodostaen samallaerilaisia yhteisöjä ja verkostoja. Näille yhteisöille on tunnusomaista, että niissä vaikuttavien jäsenien ajatustavat yhtyvät keskenään. Yhteisöissä syntyy uusia ideoita ja keksintöjä. Niiden välittäminen maailmalle on usein kuitenkin ongelmallista. Digitaalisuus, Internet ja monet muut uudet teknologiat tuovat yhden ratkaisun ongelmaan. Eräs uuden teknologian mahdollistama kanava on yhteisötelevisio, jonka kautta yhteisön viestintää voidaan tehokkaasti välittää. Yhteisöilläei kuitenkaan ole teknistä taitoa toteuttaa tällaista palvelua. Yhteisöille, kuten pk-yrityksille, kouluille, seuroille, yhdistyksille ja jopa yksittäisille ihmisille, tuleekin pystyä tarjoamaan valmis konsepti, joka on helposti heidän käytettävissään. Tämä diplomityö toimii teknisenä pohjana Finnish Satellite Television Oy:n yhteisö-tv -palvelukonseptille, joka tullaan ottamaan laajamittaiseen käyttöön vuoden 2007 aikana. Työssä käydään läpi yhteisön ja yhteisöllisyyden tunnusmerkit ja peruspiirteet, luodaan katsaus yhteisötelevision alkutaipaleisiin, nykytilaan ja sen eri ratkaisuihin. Lisäksi tutustutaan yhteisö-tv:n kansainvälisiin ja kotimaisiin kokeiluihin ja pilottiprojekteihin. Työn teknisessä osassa tutkitaan yhteisötelevision mahdollistaviin teknologioihin, siirtoteihin sekä digitaalisiin tuotantojärjestelmiin. Lopuksi työssä kootaan yhteen käytettävyydeltään, liikutettavuudeltaan ja kustannustehokkuudeltaan sopivimmat tekniset toteutusvaihtoehdot konseptin käyttöönottoa varten.

A design for an advanced architecture of satellite ground segments

This project proposes a preliminary architectural design for a control and data processing center, also known as 'ground segment', for Earth observation satellites.

Inactivation of PPARβ/δ adversely affects satellite cells and reduces postnatal myogenesis.

Peroxisome proliferator-activated receptor β/δ (PPARβ/δ) is a ubiquitously expressed gene with higher levels observed in skeletal muscle. Recently, our laboratory showed (Bonala S, Lokireddy S, Arigela H, Teng S, Wahli W, Sharma M, McFarlane C, Kambadur R. J Biol Chem 287: 12935-12951, 2012) that PPARβ/δ modulates myostatin activity to induce myogenesis in skeletal muscle. In the present study, we show that PPARβ/δ-null mice display reduced body weight, skeletal muscle weight, and myofiber atrophy during postnatal development. In addition, a significant reduction in satellite cell number was observed in PPARβ/δ-null mice, suggesting a role for PPARβ/δ in muscle regeneration. To investigate this, tibialis anterior muscles were injured with notexin, and muscle regeneration was monitored on days 3, 5, 7, and 28 postinjury. Immunohistochemical analysis revealed an increased inflammatory response and reduced myoblast proliferation in regenerating muscle from PPARβ/δ-null mice. Histological analysis confirmed that the regenerated muscle fibers of PPARβ/δ-null mice maintained an atrophy phenotype with reduced numbers of centrally placed nuclei. Even though satellite cell numbers were reduced before injury, satellite cell self-renewal was found to be unaffected in PPARβ/δ-null mice after regeneration. Previously, our laboratory had showed (Bonala S, Lokireddy S, Arigela H, Teng S, Wahli W, Sharma M, McFarlane C, Kambadur R. J Biol Chem 287: 12935-12951, 2012) that inactivation of PPARβ/δ increases myostatin signaling and inhibits myogenesis. Our results here indeed confirm that inactivation of myostatin signaling rescues the atrophy phenotype and improves muscle fiber cross-sectional area in both uninjured and regenerated tibialis anterior muscle from PPARβ/δ-null mice. Taken together, these data suggest that absence of PPARβ/δ leads to loss of satellite cells, impaired skeletal muscle regeneration, and postnatal myogenesis. Furthermore, our results also demonstrate that functional antagonism of myostatin has utility in rescuing these effects.

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Spatial and Spectral Separability of Grasslands in the inner Turku Archipelago using Landsat Thematic Mapper Satellite Imagery

The present study investigates the spatial and spectral discrimination potential for grassland patches in the inner Turku Archipelago using Landsat Thematic Mapper satellite imagery. The spatial discrimination potential was computed through overlay analysis using official grassland parcel data and a hypothetical 30 m resolution satellite image capturing the site. It found that Landsat TM imagery’s ability to retrieve pure or near-pure pixels (90% purity or more) from grassland patches smaller than 1 hectare was limited to 13% success, compared to 52% success when upscaling the resolution to 10 x 10 m pixel size. Additionally, the perimeter/area patch metric is proposed as a predictor for the suitability of the spatial resolution of input imagery. Regression analysis showed that there is a strong negative correlation between a patch’s perimeter/area ratio and its pure pixel potential. The study goes on to characterise the spectral response and discrimination potential for the five main grassland types occurring in the study area: recreational grassland, traditional pasture, modern pasture, fodder production grassland and overgrown grassland. This was done through the construction of spectral response curves, a coincident spectral plot and a contingency matrix as well as by calculating the transformed divergence for the spectral signatures, all based on training samples from the TM imagery. Substantial differences in spectral discrimination potential between imagery from the beginning of the growing season and the middle of summer were found. This is because the spectral responses for these five grassland types converge as the peak of the growing season draws nearer. Recreational grassland shows a consistent discrimination advantage over other grassland types, whereas modern pasture is most easily confused. Traditional pasture land, perhaps the most biologically valuable grassland type, can be spectrally discriminated from other grassland types with satisfactory success rates provided early growing season imagery is used.