Dataset Information

Knocking and Listening: Learning Mechanical Impulse Response for Understanding Surface Characteristics.

ABSTRACT: Inspired by spiders that can generate and sense vibrations to obtain information regarding a substrate, we propose an intelligent system that can recognize the type of surface being touched by knocking the surface and listening to the vibrations. Hence, we developed a system that is equipped with an electromagnetic hammer for hitting the ground and an accelerometer for measuring the mechanical responses induced by the impact. We investigate the feasibility of sensing 10 different daily surfaces through various machine-learning techniques including recent deep-learning approaches. Although some test surfaces are similar, experimental results show that our system can recognize 10 different surfaces remarkably well (test accuracy of 98.66%). In addition, our results without directly hitting the surface (internal impact) exhibited considerably high test accuracy (97.51%). Finally, we conclude this paper with the limitations and future directions of the study.

SUBMITTER: Ryu S

PROVIDER: S-EPMC7013596 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Knocking and Listening: Learning Mechanical Impulse Response for Understanding Surface Characteristics.

Ryu Semin S Kim Seung-Chan SC

Sensors (Basel, Switzerland) 20200109 2

Inspired by spiders that can generate and sense vibrations to obtain information regarding a substrate, we propose an intelligent system that can recognize the type of surface being touched by knocking the surface and listening to the vibrations. Hence, we developed a system that is equipped with an electromagnetic hammer for hitting the ground and an accelerometer for measuring the mechanical responses induced by the impact. We investigate the feasibility of sensing 10 different daily surfaces ...[more]

PMID: 31936449

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Project description:BackgroundSocial media platforms are increasingly being used by stakeholders to generate, access, and share health-related information and experiences. Lung cancer is the most common cancer, impacting > 2 million patients globally. This observational study utilized a social listening approach to analyze social media trends and gain insights into stakeholder perceptions of lung cancer.MethodsThis social media study retrospectively collated data from open access blogs, forums, and social networking sites. Social media posts were collected between June 2019-May 2020 from 14 European countries. Using social media aggregator tools, posts comprising lung cancer and non-small cell lung cancer-specific terms were extracted. Manual and automated relevancy algorithms filtered the extracted information to provide the relevant dataset. This contextualized dataset was further mined to generate the final data for analysis.ResultsOf 1360 conversations analyzed, 42% were generated by patients/caregivers and 14% by healthcare professionals (HCPs). A majority of patients were 51-70 years old (approximately 50%) and 91% (n = 500/550) had late-stage cancer. Treatment (35%) and disease awareness (30%) were among the most discussed topic of the patient journey. Although the overall treatment sentiment was neutral, chemotherapy was the treatment type with the highest associated negative sentiment (28%); fewer negative sentiments were associated with immunotherapy (9%) and targeted therapy (2%), due to perceptions of longer survival outcomes and fewer side effects. In conversations that discussed clinical endpoints, "survivability" and "overall survival" (47 and 30%, respectively; n = 539) were most frequently mentioned by stakeholders. HCPs mostly used technical terms, whereas patients and caregivers used colloquial terms such as "getting rid of cancer". Emotional wellness was identified to have a huge impact on quality of life in lung cancer. Delay or treatment cancellations due to COVID-19, lack of effective treatments and funding, and lack of empathy by physicians emerged as the key unmet needs among patients/caregivers.ConclusionsSocial listening proved to be an effective tool to explore stakeholders' perceptions and their key unmet needs, typically not available in published literature or databases, and provides HCPs with valuable insights into the distress, doubts, and needs of lung cancer patients and caregivers.

Dataset Information

Knocking and Listening: Learning Mechanical Impulse Response for Understanding Surface Characteristics.

Publications

Knocking and Listening: Learning Mechanical Impulse Response for Understanding Surface Characteristics.

Similar Datasets

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