Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3145
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Electrophysiological (EP) signals, referred to as low-level biopotentials driven by active or passive human movements, are of great importance for kinesiology, rehabilitation, and human-machine interaction. To capture high-fidelity EP signals, bioelectrodes should possess high conductivity, high stretchability, and high conformability to skin. While traditional metal bioelectrodes are endowed with stretchability via complex structural designs, they are vulnerable to external or internal inference due to their low fracture strain and large modulus. Here, we report a self-healing elastic composite of silver nanowire (AgNW), graphite nanosheet, and styrene--poly(ethylene-ran-butylene)--polystyrene, which exhibits high stretchability of ε = 500%, high conductivity of σ = ∼1923 S·cm, and low resistance change (Δ/) of 0.14 at ε = 40% while its resistance increases ∼0.8% after a 24 h stretching operation at ε = 50%. We employed the elastic composites for accurate and stable monitoring of electrocardiograph and surface electromyography (sEMG) signals. Further, we demonstrate an all-solution and printable process to obtain a large-scale sEMG bioelectrode array, enabling highly conformal adhesion on skin and high-fidelity gesture recognition.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/acsami.3c13942 | DOI Listing |
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