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Alan Seefeldt

Publications and source records attributed to Alan Seefeldt.

3 recordsLinked to original sources

NeckCheck: Predicting Neck Strain using Head Tracker Sensors

Tech neck, a growing musculoskeletal concern caused by prolonged poor posture during device use, has significant health implications. This study investigates the relationship between head posture and muscular activity in the upper trapezius muscle to predict muscle strain by leveraging data from EMG sensors and head trackers. We train a regression model to predict EMG envelope readings using head movement data. We conduct preliminary experiments involving various postures to explore the correlation between these modalities and assess the feasibility of predicting muscle strain using head worn sensors. We discuss the key research challenges in sensing and predicting muscle fatigue. The results highlight the potential of this approach in real-time ergonomic feedback systems, contributing to the prevention and management of tech neck.

cs.HC

NeckCare: Preventing Tech Neck using Hearable-based Multimodal Sensing

Tech neck is a modern epidemic caused by prolonged device usage and it can lead to significant neck strain and discomfort. This paper addresses the challenge of detecting and preventing tech neck syndrome using non-invasive ubiquitous sensing techniques. We present NeckCare, a novel system leveraging hearable sensors, including IMUs and microphones, to monitor tech neck postures and estimate distance form screen in real-time. By analyzing pitch, displacement, and acoustic ranging data from 15 participants, we achieve posture classification accuracy of 96% using IMU data alone and 99% when combined with audio data. Our distance estimation technique is millimeter-level accurate even in noisy conditions. NeckCare provides immediate feedback to users, promoting healthier posture and reducing neck strain. Future work will explore personalizing alerts, predicting muscle strain, integrating neck exercise detection and enhancing digital eye strain prediction.

cs.HC

Improved Panning on Non-Equidistant Loudspeakers with Direct Sound Level Compensation

Loudspeaker rendering techniques that create phantom sound sources often assume an equidistant loudspeaker layout. Typical home setups might not fulfill this condition as loudspeakers deviate from canonical positions, thus requiring a corresponding calibration. The standard approach is to compensate for delays and to match the loudness of each loudspeaker at the listener's location. It was found that a shift of the phantom image occurs when this calibration procedure is applied and one of a pair of loudspeakers is significantly closer to the listener than the other. In this paper, a novel approach to panning on non-equidistant loudspeaker layouts is presented whereby the panning position is governed by the direct sound and the perceived loudness is governed by the full impulse response. Subjective listening tests are presented that validate the approach and quantify the perceived effect of the compensation. In a setup where the standard calibration leads to an average error of 10 degrees, the proposed direct sound compensation largely returns the phantom source to its intended position.

eess.AS