Article
Nanoscience & Nanotechnology
Hu Luo, Tianhao Jin, Yu Zhang, Bohao Tian, Yuru Zhang, Dangxiao Wang
Summary: This study explores the development of a wireless and skin-integrated device for monitoring and correcting neck posture. The device features a multilayered structure that integrates all electronic components into a compact skin space. Experiments have validated the device's reliability, effectiveness, stability, and adherence during neck movement.
MICROSYSTEMS & NANOENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Mohammad Mousavi, Mohammad Alzgool, Benyamin Davaji, Shahrzad Towfighian
Summary: This paper presents two solutions for improving the performance of MEMS triboelectric vibration sensors in contact-separation mode. The first solution involves using a warped MEMS diaphragm constrained on its edges, which provides larger displacement and voltage output. The second solution involves adding constraints on the edge of the diaphragm, which increases charge density and voltage generation. These solutions show promising results in terms of sensitivity and signal-to-noise ratio improvement.
Article
Chemistry, Physical
Trapti Mudgal, Manas Tiwari, Deepak Bharti
Summary: Polystyrene-based triboelectric nanogenerators were developed and showed high voltage and power output. They were successfully applied in electronic devices and human motion monitoring.
ACS APPLIED ENERGY MATERIALS
(2022)
Article
Chemistry, Analytical
Hasnet Eftakher Ahmed, Sahereh Sahandabadi, Mohammed Jalal Ahamed
Summary: This paper investigates the feasibility of using MEMS accelerometers to measure vibration parameters related to different locations of a vehicle for automotive dynamic functions. The study compares accelerometer performances in various locations on the vehicle and analyzes the results using power spectral density, time, and frequency domain analysis. The knowledge obtained from this study can be beneficial for the control and development of vehicle diagnostics, safety, and comfort.
Article
Chemistry, Multidisciplinary
Zijian An, QiQi Fu, Jingjiang Lv, Tao Zhou, Yue Wu, Yanli Lu, Guang Liu, Zhenghan Shi, Xin li, Fenni Zhang, Qingjun Liu
Summary: Self-power wearable electronics have the potential to overcome battery limitations through harvesting energy from the environment or the human body. This study presents a wireless monitoring system driven entirely by body heat, utilizing a stretchable TEG to optimize power density and enable continuous operation of wireless wearable devices. The system demonstrates real-time monitoring of heart rate, sweat ingredients, and body motion. This advancement in self-powered wearable electronics marks a significant step towards wireless real-time health monitoring.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Engineering, Multidisciplinary
Ce Jing, Guanwen Huang, Xin Li, Qin Zhang, Huan Yang, Kai Zhang, Guolin Liu
Summary: The integration of Global Navigation Satellite System (GNSS) and accelerometers can provide more stable and reliable deformation displacement measurements by utilizing the complementary technical characteristics of these two sensors. The key to obtaining accurate solutions is the reasonable setting of measurement noise and process noise of the Kalman Filter (KF) method. However, in some complex deformation monitoring scenarios, both GNSS and accelerometers are susceptible to interference from factors like vegetation cover and external disturbance. To address this problem, an adaptive noise model based on sensors is proposed, which adjusts the measurement and process noise matrices using the covariance derived from GNSS-RTK and the standard deviation of acceleration time-varying information.
Article
Cell Biology
John R. Speakman, Yosuke Yamada, Hiroyuki Sagayama, Elena S. F. Berman, Philip N. Ainslie, Lene F. Andersen, Liam J. Anderson, Lenore Arab, Issaad Baddou, Kweku Bedu-Addo, Ellen E. Blaak, Stephane Blanc, Alberto G. Bonomi, Carlijn V. C. Bouten, Pascal Bovet, Maciej S. Buchowski, Nancy F. Butte, Stefan G. J. A. Camps, Graeme L. Close, Jamie A. Cooper, Seth A. Creasy, Sai Krupa Das, Richard Cooper, Lara R. Dugas, Cara B. Ebbeling, Ulf Ekelund, Sonja Entringer, Terrence Forrester, Barry W. Fudge, Annelies H. Goris, Michael Gurven, Catherine Hambly, Asmaa El Hamdouchi, Marije B. Hoos, Sumei Hu, Noorjehan Joonas, Annemiek M. Joosen, Peter Katzmarzyk, Kitty P. Kempen, Misaka Kimura, William E. Kraus, Robert F. Kushner, Estelle Lambert, William R. Leonard, Nader Lessan, David S. Ludwig, Corby K. Martin, Anine C. Medin, Erwin P. Meijer, James C. Morehen, James P. Morton, Marian L. Neuhouser, Theresa A. Nicklas, Robert M. Ojiambo, Kirsi H. Pietilainen, Yannis P. Pitsiladis, Jacob Plange-Rhule, Guy Plasqui, Ross L. Prentice, Roberto A. Rabinovich, Susan B. Racette, David A. Raichlen, Eric Ravussin, Rebecca M. Reynolds, Susan B. Roberts, Albertine J. Schuit, Anders M. Sjodin, Eric Stice, Samuel S. Urlacher, Giulio Valenti, Ludo M. Van Etten, Edgar A. Van Mil, Jonathan C. K. Wells, George Wilson, Brian M. Wood, Jack Yanovski, Tsukasa Yoshida, Xueying Zhang, Alexia J. Murphy-Alford, Cornelia U. Loechl, Edward L. Melanson, Amy H. Luke, Herman Pontzer, Jennifer Rood, Dale A. Schoeller, Klaas R. Westerterp, William W. Wong
Summary: The study showed that the use of different equations may introduce considerable variability in estimating total energy expenditure. Based on validation studies, the authors proposed a new equation for estimating rCO(2) sensitive to dilution space ratio and found DSR decreases at body masses below 10 kg.
CELL REPORTS MEDICINE
(2021)
Article
Engineering, Biomedical
Jonathan T. Alvarez, Lucas F. Gerez, Oluwaseun A. Araromi, Jessica G. Hunter, Dabin K. Choe, Christopher J. Payne, Robert J. Wood, Conor J. Walsh
Summary: The force-generating capacity of skeletal muscle is crucial for evaluating musculoskeletal health. Traditional hardware for strength evaluation has limitations, while wearable soft strain sensors can continuously monitor muscle deformation, providing a richer dataset for strength assessment.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2022)
Article
Robotics
Jinlin Liu, Yanan Yang, Jie Peng, Haicheng Wang, Da Chen, Yijian Liu, Lina Yang, Huining Chen
Summary: This study introduces a high-sensitivity fully soft capacitive pressure sensor with bionic spine-pillar microstructure, showcasing good deformability and a broad linear pressure dynamic range. The sensor utilizes a combination of microscale spines and millimeter-sized pillar array, and a simple equivalent circuit model to demonstrate sensing mechanism and geometric effect, successfully monitoring various skin movements in practical applications.
Article
Chemistry, Multidisciplinary
Jean-Baptiste Tylcz, Max Schreiber, Dominik Michalski, Joseph Classen, Galina Ivanova
Summary: Daily physical activity is crucial for improving health and preventing chronic diseases and acute events. This paper proposes a modified method using gravity estimation to compensate for inaccurate sensors and enable the use of low sampled wrist accelerometer data for physical activity detection and quantification in daily live environments. The algorithm was evaluated on healthy subjects and showed the ability to discriminate between low, moderate, and high intensity activities.
APPLIED SCIENCES-BASEL
(2023)
Article
Multidisciplinary Sciences
Ramon Boekesteijn, Jose Smolders, Vincent Busch, Noel Keijsers, Alexander Geurts, Katrijn Smulders
Summary: Inertial sensors show promise in objectively measuring gait recovery after total knee and hip arthroplasty, and compared to patient-reported outcome measures (PROMs). Gait parameters recover to healthy levels after both surgeries, with differences in recovery trajectories between gait parameters and PROMs at two months post-operatively. This highlights the complementary information provided by sensor-derived gait parameters for evaluating physical function.
Article
Chemistry, Analytical
Yoshimasa Sagawa, Eric Watelain, Thierry Moulin, Pierre Decavel
Summary: This study found that the level of activity in persons with multiple sclerosis (PwMS) during weekdays and weekends was significantly lower than the healthy control group. The level of activity was negatively correlated with clinical parameters such as multiple sclerosis disability in PwMS.
Article
Chemistry, Physical
Trilochan Bhatta, Pukar Maharjan, Kumar Shrestha, Sanghyun Lee, Md Salauddin, M. Toyabur Rahman, S. M. Sohel Rana, Sudeep Sharma, Chani Park, Sang Hyuk Yoon, Jae Yeong Park
Summary: This research introduces a novel approach that utilizes wave energy to generate power and wirelessly transmit information, enhancing the real-time and continuous monitoring of the marine environment. By integrating self-powered wave motion sensors and generators through a specially designed device structure, a self-sustained solution for marine environment monitoring is provided.
ADVANCED ENERGY MATERIALS
(2022)
Article
Engineering, Electrical & Electronic
Yanjie Zhu, Hidehiko Sekiya, Takayuki Okatani, Ikumasa Yoshida, Shuichi Hirano
Summary: The paper proposes a vehicle monitoring solution for acceleration-based bridge weigh-in-motion system using deep learning and wavelet transform methods. By dividing the monitoring task into three subtasks, the proposed method improves computational efficiency and generalization capability. Evaluation on a multi-lane highway bridge in Tokyo shows that the method can accurately identify vehicles and driving lanes efficiently.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Information Systems
Hana Charvatova, Ales Prochazka, Oldrich Vysata, Carmen Paz Suarez-Araujo, Jonathan Hurndall Smith
Summary: Motion pattern analysis in cycling was conducted using various sensors and computational tools to study the relationships between heart rate, accelerometric signals, and geographical data, with the use of artificial intelligence for classification. The results showed promising accuracy in classifying downhill and uphill cycling based on accelerometric data, suggesting the potential application of these methods in various sports activities and healthcare fields.
