Dataset Information

Multifunctional Stretchable Sensors for Continuous Monitoring of Long-Term Leaf Physiology and Microclimate.

ABSTRACT: Communication with plants to understand their growth mechanisms and interaction with the surrounding environment may improve production yield in agriculture and facilitate prevention of plant diseases and negative influence of environmental stress. Typical sensing technologies in plant biology and precision agriculture largely rely on techniques with low spatial and temporal resolutions, and fail to continuously and precisely determine localized variation in leaf physiology and microenvironments. Here, techniques to develop a multifunctional stretchable leaf-mounted sensor have been developed to offer optimized adaptability to plant growth and monitor leaf physiological and environmental conditions in continuous and highly sensitive manners. The multifunctional leaf sensor contains multiple heterogeneous sensing elements made of metal, carbon nanotube matrix, and silicon, leading to temperature, hydration, light illuminance, and strain sensing capabilities on a leaf. Evaluation under a controlled environment indicates excellent precision and accuracy of the sensor compared to conventional devices. Furthermore, indoor and outdoor experiments have demonstrated the multifunctional monitoring ability of the sensor in real situations. The multifunctional stretchable sensor holds the promise to advance monitoring techniques in plant biology and precision agriculture, resulting in improved capability to record slow and subtle physiological changes in plants and plant/environment interaction.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC6648038 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Multifunctional Stretchable Sensors for Continuous Monitoring of Long-Term Leaf Physiology and Microclimate.

Zhao Yicong Y Gao Shenghan S Zhu Jia J Li Jiameng J Xu Hang H Xu Kexin K Cheng Huanyu H Huang Xian X

ACS omega 20190530 5

Communication with plants to understand their growth mechanisms and interaction with the surrounding environment may improve production yield in agriculture and facilitate prevention of plant diseases and negative influence of environmental stress. Typical sensing technologies in plant biology and precision agriculture largely rely on techniques with low spatial and temporal resolutions, and fail to continuously and precisely determine localized variation in leaf physiology and microenvironments ...[more]

PMID: 31460042

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Project description:Parkinson's disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient's condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients' status and the disease's symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson's, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms' assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.

Dataset Information

Multifunctional Stretchable Sensors for Continuous Monitoring of Long-Term Leaf Physiology and Microclimate.

Publications

Multifunctional Stretchable Sensors for Continuous Monitoring of Long-Term Leaf Physiology and Microclimate.

Similar Datasets

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