Search results for "IKEA"
showing 10 items of 103 documents
Comparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation
2020
Abstract Modulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli. Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants. Both tactile and proprioceptive st…
Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults
2020
Gait variability observed in step duration is predictive of impending adverse health outcomes among apparently healthy older adults and could potentially be evaluated using wearable sensors (inertial measurement units, IMU). The purpose of the present study was to establish the reliability and concurrent validity of gait variability and complexity evaluated with a waist and an ankle-worn IMU. Seventeen women (age 74.8 (SD 44) years) and 10 men (73.7 (4.1) years) attended two laboratory measurement sessions a week apart. Their stride duration variability was concurrently evaluated based on a continuous 3 min walk using a force plate and a waist- and an ankle-worn IMU. Their gait complexity (…
Using deep neural networks for kinematic analysis: Challenges and opportunities
2020
Kinematic analysis is often performed in a lab using optical cameras combined with reflective markers.\ud With the advent of artificial intelligence techniques such as deep neural networks, it is now possible\ud to perform such analyses without markers, making outdoor applications feasible. In this paper I summarise\ud 2D markerless approaches for estimating joint angles, highlighting their strengths and limitations.\ud In computer science, so-called ‘‘pose estimation” algorithms have existed for many years. These methods\ud involve training a neural network to detect features (e.g. anatomical landmarks) using a process called\ud supervised learning, which requires ‘‘training” images to be …
Decoding Individual differences and musical preference via music-induced movement.
2022
AbstractMovement is a universal response to music, with dance often taking place in social settings. Although previous work has suggested that socially relevant information, such as personality and gender, are encoded in dance movement, the generalizability of previous work is limited. The current study aims to decode dancers’ gender, personality traits, and music preference from music-induced movements. We propose a method that predicts such individual difference from free dance movements, and demonstrate the robustness of the proposed method by using two data sets collected using different musical stimuli. In addition, we introduce a novel measure to explore the relative importance of dif…
Predicting ACL Injury Using Machine Learning on Data From an Extensive Screening Test Battery of 880 Female Elite Athletes
2022
Background: Injury risk prediction is an emerging field in which more research is needed to recognize the best practices for accurate injury risk assessment. Important issues related to predictive machine learning need to be considered, for example, to avoid overinterpreting the observed prediction performance. Purpose: To carefully investigate the predictive potential of multiple predictive machine learning methods on a large set of risk factor data for anterior cruciate ligament (ACL) injury; the proposed approach takes into account the effect of chance and random variations in prediction performance. Study Design: Case-control study; Level of evidence, 3. Methods: The authors used 3-dime…
Katsaus Scandinavian Economic History Review -aikakauskirjassa vuosina 2003-2012 ilmestyneeseen tutkimukseen
2014
Tässä työssä tutkitaan liikearkistojen käyttöä historiantutkimuksen lähteinä. Työssä selvitetään muun muassa millaista liikearkistoja hyödyntävä tutkimus nykypäivänä on, millaisia aiheita siinä tutkitaan ja mihin ajanjaksoihin tutkimus painottuu. Työssä selvitetään myös minkä tyyppisiä liikearkistoja tutkimus lähteinään käyttää ja mitkä muistiorganisaatiot liikearkistoja säilyttävät. Lisäksi työssä esitellään Suomessa, Ruotsissa ja Tanskassa toimivat liikearkistoja keräävät keskusarkistot Elinkeinoelämän Keskusarkisto, Centrum för Näringslivshistoria ja Erhvervsarkivet. Työssä myös vertaillaan tutkimuksen käyttämiä arkistolähteitä ja keskusarkistojen materiaalia ajallisen ja toimialoittaise…
Historic constructions of the early multinational: on power, politics and culture in Pan Am narratives
2018
This paper examines how Pan American World Airways (Pan Am) - an early incarnation of a multinational enterprise (MNE) - developed its image as an international company. In particular, we examine how the company developed and managed potentially conflicting narratives, including the modernising US company and the airline of 'the Americas' (specifically South America); the carrier of US national interests and the politically neutral actor serving to unify cultures; the purveyor of exotic experiences and the pioneer of modernism. Through a focus on organisational narratives, we reveal the powerful influence of such story telling (through design and serendipity) on images of the peoples and co…
Markerless 2D kinematic analysis of underwater running : A deep learning approach
2018
Kinematic analysis is often performed with a camera system combined with reflective markers placed over bony landmarks. This method is restrictive (and often expensive), and limits the ability to perform analyses outside of the lab. In the present study, we used a markerless deep learning-based method to perform 2D kinematic analysis of deep water running, a task that poses several challenges to image processing methods. A single GoPro camera recorded sagittal plane lower limb motion. A deep neural network was trained using data from 17 individuals, and then used to predict the locations of markers that approximated joint centres. We found that 300–400 labelled images were sufficient to tra…
Ikea e altre semiosfere. Laboratorio di sociosemiotica
2019
Da quando l’uomo è diventato sapiens sapiens, la vita non ha a che fare solo con la biosfera ma anche con la semiosfera. Con questo termine ci riferiamo ancora a un insieme di elementi eterogenei che hanno la capacità di produrne altri, solo che tali elementi non hanno una natura chimica o biologica, hanno invece a che fare con le straordinarie capacità mentali che l’uomo possiede. Possiamo allora immaginarci questo spazio popolato da prodotti culturali di varia natura: parole, immagini, discorsi, ma anche oggetti, edifici, abiti, cibo, dove a rendere tali elementi parte del sistema non è unicamente la loro natura materiale, peraltro molto diversa, ma la cosa che di volta in volta li accomu…
Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity
2020
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem. Kinematic data, namely a number of raw signals in the sagittal plane, collected by the Vicon motion capture system (Oxford Metrics Group, UK) were employed as predictors. Therefore, the input data for the predictive model are presented as a multi-channel time series. Deep learning techniques, namely five convolutional neural network (CNN) models were applied to the binary classification analysis, based on a Multi-Layer Perceptron (MLP) classifi…