Ecological Sucking Monitoring of Newborns

Taffoni, Fabrizio; Tamilia, Eleonora; Palminteri, Maria Rosaria; Schena, Emiliano; Formica, Domenico; Delafield‐Butt, Jonathan; Keller, Flavio; Silvestri, Sergio; Guglielmelli, Eugenio

doi:10.1109/jsen.2013.2271585

Cited by 19 publications

(10 citation statements)

References 39 publications

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“…Microneurography and sEMG signals were recorded at a sampling rate of 10,000 Hz with a 16-bits data acquisition board (National Instruments PCI-6251), installed on a personal computer (PC) running a custom program written in Labview 2012 that handled the recording and the real-time processing assisting the neurologist in seeking the fibers. The pressure sensor was custom-made [24] and constituted by an airtight sphere-catheter system connected to a Programmable Interface Controller at its turn connected to the PC by a serial port. The recording of its data was performed at a sampling rate of 10 Hz and controlled by the aforementioned custom program.…”

Section: Methodsmentioning

confidence: 99%

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

et al. 2019

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Background The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the processing of descending efferent neural signals recorded using peripheral neural interfaces could be a solution to such limitation. Unfortunately, this choice is still restrained by the reduced knowledge of the dynamics of human efferent signals recorded from the nerves and associated to hand movements. Findings To address this issue, in this work we acquired neural efferent activities from healthy subjects performing hand-related tasks using ultrasound-guided microneurography, a minimally invasive technique, which employs needles, inserted percutaneously, to record from nerve fibers. These signals allowed us to identify neural features correlated with force and velocity of finger movements that were used to decode motor intentions. We developed computational models, which confirmed the potential translatability of these results showing how these neural features hold in absence of feedback and when implantable intrafascicular recording, rather than microneurography, is performed. Conclusions Our results are a proof of principle that microneurography could be used as a useful tool to assist the development of more effective hand prostheses. Electronic supplementary material The online version of this article (10.1186/s12938-019-0659-9) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

et al. 2019

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“…Figure 1 reports a typical 10 s pressure burst: experimental data, acquired on healthy subjects and reported in [ 23 ], showed that intraoral pressure is in the range of [−140,+15] mmHg. The bandwidth of the pressure signal was estimated, calculating its Power Spectral Density (PSD) by means of the Welch overlapped segmented average: it may be considered well below 20 Hz.…”

Section: Nutritive Sucking Processmentioning

confidence: 99%

Technological Solutions and Main Indices for the Assessment of Newborns’ Nutritive Sucking: A Review

Tamilia

Taffoni

Formica

et al. 2014

Sensors

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Nutritive Sucking (NS) is a highly organized process that is essential for infants' feeding during the first six months of their life. It requires the complex coordination of sucking, swallowing and breathing. The infant's inability to perform a safe and successful oral feeding can be an early detector of immaturity of the Central Nervous System (CNS). Even though the importance of early sucking measures has been confirmed over the years, the need for standardized instrumental assessment tools still exists. Clinicians would benefit from specifically designed devices to assess oral feeding ability in their routine clinical monitoring and decision-making process. This work is a review of the main instrumental solutions developed to assess an infant's NS behavior, with a detailed survey of the main quantities and indices measured and/or estimated to characterize sucking behavior skills and their development. The adopted sensing measuring systems will be described, and their main advantages and weaknesses will be discussed, taking into account their application to clinical practice, or to at-home monitoring as post-discharge assessment tools. Finally, the study will highlight the most suitable sensing solutions and give some prompts for further research.

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“…Each suck is composed of an Increasing Suction (IS) phase, followed by a change in pressure in the opposite direction giving a Decreasing Suction (DS) phase [3]. The bandwidth of the pressure signal can be considered below 20 Hz according to previous results obtained from the analysis of the Power Spectral Density, reported in [12]. Thus, pressure signals have been low-pass filtered with a cut-off frequency equal to 20 Hz.…”

Section: Signal Analysismentioning

confidence: 99%

An automatized system for the assessment of nutritive sucking behavior in infants: A preliminary analysis on term neonates

Tamilia

Delafield

Fiore

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Nutritive Sucking (NS) is a highly organized process that can reflect infants' maturation during the early post-natal period. The assessment of NS may provide a sensitive means of evaluating early motor skills and their development. Thus, a reliable tool for assessing sucking behavior may benefit diagnostics and treatment of newborns since the first days of life. The aim of this work is to propose an automatized system to measure sucking ability and calculate a set of objective and quantitative indices for its assessment. We focused on the analysis of the Intraoral Pressure (IP) generated by infants while feeding: an ad-hoc designed software application was developed to analyze the signal obtained by a pressure transducer connected with a catheter placed through a standard bottle teat into the oral cavity during feeding. Automatic algorithms for suck and burst identification and for their characterization are described. We carried out a preliminary test of the system, analyzing data from two healthy term newborns, tested twice over time (1-2 days old and 6-10 weeks later). We calculated a set of different sucking parameters (e.g. sucking amplitude, frequency and area), and proposed some indices, that are typically used for the assessment of motor control, in order to assess the smoothness of IP. Results encourage further investigation of the proposed system for monitoring the development of early sucking skills.

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Ecological Sucking Monitoring of Newborns

Cited by 19 publications

References 39 publications

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

Technological Solutions and Main Indices for the Assessment of Newborns’ Nutritive Sucking: A Review

An automatized system for the assessment of nutritive sucking behavior in infants: A preliminary analysis on term neonates

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