Evidence map›Paper›PMID 32825829›Full record

ArticleJournal of neuroengineering and rehabilitation2020

Traumatic brain injury neuroelectrochemical monitoring: behind-the-ear micro-instrument and cloud application.

Momen K Tageldeen, Sally A N Gowers, Chi L Leong, Martyn G Boutelle, Emmanuel M Drakakis

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Momen K TageldeenBioinspired VLSI Circuits and Systems Group, Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
Sally A N GowersBiomedical Sensors Group, Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
Chi L LeongBiomedical Sensors Group, Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
Martyn G BoutelleBiomedical Sensors Group, Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
Emmanuel M DrakakisBioinspired VLSI Circuits and Systems Group, Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UK. e.drakakis@imperial.ac.uk.ORCID 0000-0001-6649-0573

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraumatic Brain Injury (TBI) is a leading cause of fatality and disability worldwide, partly due to the occurrence of secondary injury and late interventions. Correct diagnosis and timely monitoring ensure effective medical intervention aimed at improving clinical outcome. However, due to the limitations in size and cost of current ambulatory bioinstruments, they cannot be used to monitor patients who may still be at risk of secondary injury outside the ICU.

methodsWe propose a complete system consisting of a wearable wireless bioinstrument and a cloud-based application for real-time TBI monitoring. The bioinstrument can simultaneously record up to ten channels including both ECoG biopotential and neurochemicals (e.g. potassium, glucose and lactate), and supports various electrochemical methods including potentiometry, amperometry and cyclic voltammetry. All channels support variable gain programming to automatically tune the input dynamic range and address biosensors' falling sensitivity. The instrument is flexible and can be folded to occupy a small space behind the ear. A Bluetooth Low-Energy (BLE) receiver is used to wirelessly connect the instrument to a cloud application where the recorded data is stored, processed and visualised in real-time. Bench testing has been used to validate device performance.

resultsThe instrument successfully monitored spreading depolarisations (SDs) - reproduced using a signal generator - with an SNR of 29.07 dB and NF of 0.26 dB. The potentiostat generates a wide voltage range from -1.65V to +1.65V with a resolution of 0.8mV and the sensitivity of the amperometric AFE was verified by recording 5 pA currents. Different potassium, glucose and lactate concentrations prepared in lab were accurately measured and their respective working curves were constructed. Finally,the instrument achieved a maximum sampling rate of 1.25 ksps/channel with a throughput of 105 kbps. All measurements were successfully received at the cloud.

conclusionThe proposed instrument uniquely positions itself by presenting an aggressive optimisation of size and cost while maintaining high measurement accuracy. The system can effectively extend neuroelectrochemical monitoring to all TBI patients including those who are mobile and those who are outside the ICU. Finally, data recorded in the cloud application could be used to help diagnosis and guide rehabilitation.

Indexed as

Brain Injuries, TraumaticBiosensing TechniquesBrain ChemistryElectrocorticographyHumansMaleMonitoring, AmbulatoryNeurophysiological MonitoringCloud processingFlexible PCBMicrodialysisTraumatic brain injury (TBI)Wireless brain monitoring

Identifiers

PMID32825829
PMCPMC7441655

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.