2020
DOI: 10.1016/j.talanta.2020.120757
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Simultaneous detection of salivary Δ9-tetrahydrocannabinol and alcohol using a Wearable Electrochemical Ring Sensor

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Cited by 106 publications
(70 citation statements)
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“…Virtual delivery of CM using remote verification of substance use is under evaluation as a remotely delivered treatment for alcohol use ( NCT03883126 ), with promising preliminary findings ( Koffarnus, Kablinger, Swallow, & Bickel, 2015 ). Abstinence verification technologies for alcohol use include remote breath sensors ( Keays, 2014 ; Ofir, Navon, Yichie, & Biron, 2014 ) and wearables ( Fairbairn & Kang, 2019 ; Flango & Cheesman, 2009 ); and development is underway for wearables and remote sensors to detect cocaine ( Holtyn et al, 2019 ), nicotine ( Imtiaz, Ramos-Garcia, Wattal, Tiffany, & Sazonov, 2019 ; Tai et al, 2020 ), cannabis ( Mishra et al, 2020 ), and simultaneous use of multiple substances ( Xue et al, 2020 ). Research is necessary to: 1) support deploying CM into virtual care, including evaluating the feasibility and effectiveness of remotely delivered CM for a variety of SUDs, and 2) develop implementation strategies to embed remote CM into existing clinics sustainably.…”
Section: Behavioral Economic Interventions Are Well-suited For Virtuamentioning
confidence: 99%
“…Virtual delivery of CM using remote verification of substance use is under evaluation as a remotely delivered treatment for alcohol use ( NCT03883126 ), with promising preliminary findings ( Koffarnus, Kablinger, Swallow, & Bickel, 2015 ). Abstinence verification technologies for alcohol use include remote breath sensors ( Keays, 2014 ; Ofir, Navon, Yichie, & Biron, 2014 ) and wearables ( Fairbairn & Kang, 2019 ; Flango & Cheesman, 2009 ); and development is underway for wearables and remote sensors to detect cocaine ( Holtyn et al, 2019 ), nicotine ( Imtiaz, Ramos-Garcia, Wattal, Tiffany, & Sazonov, 2019 ; Tai et al, 2020 ), cannabis ( Mishra et al, 2020 ), and simultaneous use of multiple substances ( Xue et al, 2020 ). Research is necessary to: 1) support deploying CM into virtual care, including evaluating the feasibility and effectiveness of remotely delivered CM for a variety of SUDs, and 2) develop implementation strategies to embed remote CM into existing clinics sustainably.…”
Section: Behavioral Economic Interventions Are Well-suited For Virtuamentioning
confidence: 99%
“…A novel sensor ring concept, comprising a powerful wireless electronic board embedded into a ring platform and a readily replaceable printed dual-sensor electrode cap, was developed for the simultaneous, direct and rapid field detection of D9-tetrahydrocannabinol (THC) and alcohol in diluted saliva [ 86 ]. The ring sensing platform contained a voltammetric THC sensor based on a multi-walled carbon nanotubes MWCNTs/carbon electrode and an amperometric alcohol biosensor involving Prussian-blue (PB) mediator, coated with AOx/chitosan reagent layer on the ring cap ( Figure 11 b).…”
Section: Wearable Printed Electrodes For Biosensing Applicationsmentioning
confidence: 99%
“…SPEs fabricated on a temporary tattoo ( e ), bendable bandage ( f ), textile substrate ( g ), glove ( h ), water-soluble silk thin-film substrates (transferred to tooth enamel) ( i ), contact lens ( j ), or incorporated in a mouthguard ( k ), eyeglasess ( l ) or ring ( m ). Reprinted and adapted with permission of Springer [ 68 ] ( e , j , k ) Wiley [ 81 ] ( f ), Elsevier [ 82 ] ( a , g ), Elsevier [ 82 ]( b ), Wiley [ 83 ] ( c ), Wiley [ 65 ] ( h ), Nature Research [ 84 ] ( i ), Elsevier [ 85 ] ( l ), and Elsevier [ 86 ] ( c , m ).…”
Section: Figurementioning
confidence: 99%
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“…There are wearable technologies that allow for biosensing of metabolites in sweat [ 74 , 75 ]; however, they have a long delay, some up to two hours, that makes them useless for on-site Driving While Intoxicated (DWI) analysis. Similar research has looked into saliva for the identification of tetrahydrocannabinol (THC) [ 76 ] and an overall approach that analyzes multiple types of legal and illegal compounds in sweat [ 77 ].…”
Section: Introductionmentioning
confidence: 99%