ATLANE – Seite 2

WireGuard Client for Synology DSM

By J.D. Dezember 12, 2023

Unfortunately, as of now, there is still no native integration of the WireGuard protocol for the Synology NAS series. However, it is possible to retrofit this feature. WireGuard is a modern VPN protocol known for its simplicity and high performance. It was designed to be faster, simpler, and more streamlined than existing VPN solutions like IPSec and OpenVPN. WireGuard employs advanced cryptography and runs as a kernel module, meaning it operates directly within the operating…

.informatik

Install Azure-Kinect-SDK 1.4 on Ubuntu 22.04

By J.D. November 15, 2023

.informatik

UMAP – “Uniform Manifold Approximation and Projection” und die Riemannschen Mannigfaltigkeiten

By J.D. Oktober 29, 2023

UMAP, kurz für “Uniform Manifold Approximation and Projection”, ist eine starke Methode zur Dimensionsreduktion und hat sich in der Datenwissenschaft rasch einen Namen gemacht. Im Gegensatz zu anderen gängigen Techniken, wie zum Beispiel t-SNE, basiert UMAP auf soliden mathematischen Grundlagen und bietet sowohl Geschwindigkeit als auch Flexibilität. Es wurde entwickelt, um hochdimensionale Daten in einen niedrigeren Dimensionenraum zu projizieren, wobei die ursprünglichen Abstände zwischen den Datenpunkten so gut wie möglich beibehalten werden. Dies ist…

.gekritzel

Universum 25: Ein Blick in die dystopische Welt von John Calhouns Ratten-Utopie bei sozialem Dichtestress

By J.D. Oktober 15, 2023

Das Experiment „Universum 25“, durchgeführt von dem amerikanischen Ethologen John B. Calhoun, stellt einen Meilenstein in der Verhaltensforschung und Soziologie dar. Calhouns Forschungsarbeit, die in den 1960er und 1970er Jahren durchgeführt wurde, bietet ein beeindruckendes wie auch beunruhigendes Bild über das Verhalten von Gesellschaften unter Bedingungen extremer Dichte und unendlicher Ressourcen. Der Anfang von Universum 25 Die zentrale Idee hinter dem Experiment war die Schaffung einer „Mäuse-Utopie“, einem Lebensraum, in dem Nager unter „paradiesischen“ Bedingungen…

.gekritzel

Polemik bringt uns in der Gesundheitsdebatte nicht weiter

By J.D. Oktober 3, 2023

Herr Prof. Lauterbach, “Am Brückentag schließen viele Praxen, wie die Apotheker wollen auch sie mehr Geld. Im Mittel (Median) verdienen sie aber nach Abzug aller Kosten um die 230.000 Euro pro Jahr. Soll der Beitragssatz für Arbeitnehmer steigen damit das Honorar weiter steigt?” – Twitter: Prof. Karl Lauterbach 1.10.23 Was an Ihrem Tweet befremdet, ist der entstehende Eindruck, Sie würden Gruppen gezielt gegeneinander aufbringen wollen, indem Sie Hintergrundwissen, das Ihnen zweifelsohne bekannt sein muss, bewusst…

Abstract : Postural instability is a common complication in advanced Parkinson’s disease (PD) associated with recurrent falls and fall-related injuries. The test of retropulsion, consisting of a rapid balance perturbation by a pull in the backward direction, is regarded as the gold standard for evaluating postural instability in PD and is a key component of the neurological examination and clinical rating in PD (e.g., MDS-UPDRS). However, significant variability in test execution and interpretation contributes to a low intra- and inter-rater test reliability. Here, we explore the potential for objective, vision-based assessment of the pull test (vPull) using 3D pose tracking applied to single-sensor RGB-Depth recordings of clinical assessments. The initial results in a cohort of healthy individuals (n = 15) demonstrate overall excellent agreement of vPull-derived metrics with the gold standard marker-based motion capture. Subsequently, in a cohort of PD patients and controls (n = 15 each), we assessed the inter-rater reliability of vPull and analyzed PD-related impairments in postural response (including pull-to-step latency, number of steps, retropulsion angle). These quantitative metrics effectively distinguish healthy performance from and within varying degrees of postural impairment in PD. vPull shows promise for straightforward clinical implementation with the potential to enhance the sensitivity and specificity of postural instability assessment and fall risk prediction in PD. ... read on

Abstract : Mobile health technologies enable continuous, quantitative assessment of mobility and gait in real-world environments, facilitating early diagnosis of gait disorders, disease progression monitoring, and prediction of adverse events like falls. Traditionally, mobile gait assessment predominantly relied on body-fixed sensors positioned at the feet or lower trunk. Here, we investigate the potential of an algorithm utilizing an ear-worn motion sensor for spatiotemporal segmentation of gait patterns. We collected 3D acceleration profiles from the ear-worn sensor during varied walking speeds in 53 healthy adults. Temporal convolutional networks were trained to detect stepping sequences and predict spatial relations between steps. The resulting algorithm, mEar, accurately detects initial and final ground contacts (F1 score of 99% and 91%, respectively). It enables determination of temporal and spatial gait cycle characteristics (among others stride time and stride length) with good to excellent validity at a precision sufficient to monitor clinically relevant changes in walking speed, stride-to-stride variability, and side asymmetry. This study highlights the ear as a viable site for monitoring gait and proposes its potential integration with in-ear vital sign monitoring. Such integration offers a practical approach to comprehensive health monitoring and telemedical applications, by integrating multiple sensors in a single anatomical location. ... read on

Abstract : Human activity recognition (HAR) technology enables continuous behavior monitoring, which is particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these activities while under monitoring. Various machine learning algorithms, ranging from interpretable shallow models to state-of-the-art deep learning approaches designed for HAR (i.e., DeepConvLSTM and ConvTransformer), were employed for classification. The results demonstrate the ear sensor’s efficacy, with deep learning models achieving a 98% accuracy rate of classification. The obtained classification models are agnostic regarding which ear the sensor is worn and robust against moderate variations in sensor orientation (e.g., due to differences in auricle anatomy), meaning no initial calibration of the sensor orientation is required. The study underscores the ear’s efficacy as a suitable site for monitoring human daily activity and suggests its potential for combining HAR with in-ear vital sign monitoring. This approach offers a practical method for comprehensive health monitoring by integrating sensors in a single anatomical location. This integration facilitates individualized health assessments, with potential applications in tele-monitoring, personalized health insights, and optimizing athletic training regimes. ... read on

WireGuard Client for Synology DSM

Install Azure-Kinect-SDK 1.4 on Ubuntu 22.04

UMAP – “Uniform Manifold Approximation and Projection” und die Riemannschen Mannigfaltigkeiten

Universum 25: Ein Blick in die dystopische Welt von John Calhouns Ratten-Utopie bei sozialem Dichtestress

Polemik bringt uns in der Gesundheitsdebatte nicht weiter

Precision Balance Assessment in Parkinson’s Disease: Utilizing Vision-Based 3D Pose Tracking for Pull Test Analysis

Mobile Spatiotemporal Gait Segmentation Using an Ear-Worn Motion Sensor and Deep Learning

Human activity recognition in a free-living environment using an ear-worn motion sensor