Browsing by Author "Guo, Yuzhu"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Open Access Editorial: New theories, models, and AI methods of brain dynamics, brain decoding and neuromodulation(Frontiers, 2023-12-12) Guo, Yuzhu; Li, Yang; Wei, Hua-Liang; Zhao, YifanThe human brain is highly dynamic and complex, supporting a remarkable range of functions by dynamically integrating and coordinating different brain regions and networks across multiple spatial and temporal scales. Research on the human brain has become truly interdisciplinary involving medicine, neurobiology, engineering, and related fields. A thorough understanding of the mechanisms of neuromodulation actions is urgently needed for stimulation parameters optimization, response prediction, and consistent therapy. This Research Topic aims to combine top-down and bottom-up methods to produce robust results that allow for a meaningful interpretation in terms of the underlying brain dynamics with an emphasis on brain decoding and neuromodulation.Item Open Access EEG signal processing techniques and applications(MDPI, 2023-11-09) Zhao, Yifan; He, Fei; Guo, YuzhuItem Open Access A new proxy measurement algorithm with application to the estimation of vertical ground reaction forces using wearable sensors(MDPI, 2017-09-22) Guo, Yuzhu; Storm, Fabio; Zhao, Yifan; Billings, Stephen A.; Pavic, Aleksandar; Mazzà, Claudia; Guo, Ling-ZhongMeasurement of the ground reaction forces (GRF) during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF) from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR) is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0%) using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra). Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.