12 bit analog to digital converter

Manufactured by National Instruments

Sourced in United States

The 12-bit analog-to-digital converter is a data acquisition device that converts continuous analog signals into digital data. It has a resolution of 12 bits, allowing it to represent analog input voltages with 4,096 discrete digital values. The device can sample and digitize analog signals at a specific rate, providing a digital representation of the original analog waveform.

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Lab products found in correlation

Labview, by National Instruments (4 mentions) Matlab, by MathWorks (2 mentions) Sc 24, by SCIREQ (1 mentions) Bagnoli 16 channel emg system, by Delsys (1 mentions) De 2.1 single differential surface emg sensor, by Delsys (1 mentions)

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Analog-to-digital converter (5 citations)

9 protocols using 12 bit analog to digital converter

Isometric Strength and EMG Measurement

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During the isometric strength testing, force was detected by the tension applied to the load cell. The force signal was digitized with a 12-bit analog-to-digital converter (National Instruments, Austin, TX, USA) and stored in a personal computer for further analyses. Bipolar EMG signals were detected from the belly of the biceps brachii muscle with a preamplified surface EMG sensor (10 mm interelectrode distance DE 2.1 single differential surface EMG sensor; Delsys, Inc., Boston, MA, USA) during all the isometric MVCs. Before placing the surface EMG sensor, all skin sites were shaved and cleansed with rubbing alcohol. The EMG sensor was placed in accordance to the electrode placement recommendations from the SENIAM project [24 ], and the reference electrode (5.08 cm diameter; Dermatrode HE-R, American Imex, Irvine, CA, USA) was placed on the seventh cervical vertebra. The raw EMG signals were amplified (gain = 1000) with Bagnoli 16-channel EMG system (Delsys, Inc., Boston, MA, USA) and filtered with a bandpass of 10-500 Hz. The EMG signals were then digitized at a sampling rate of 20000 samples per second with a 12-bit analog-to-digital converter (National Instruments, Austin, TX, USA) and stored in a personal computer for subsequent analyses.

Ye X., Beck T, & Wages N. (2015). Reduced susceptibility to eccentric exercise-induced muscle damage in resistance-trained men is not linked to resistance training-related neural adaptations. Biology of Sport, 32(3), 199-205.

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Paretic Leg Muscle EMG Monitoring

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Surface electrodes (Delsys DE 2.1, Delsys Inc, Boston, MA) were used to record the electromyograms (EMG) from paretic leg muscles: hip abductor (gluteus medius), medial hamstrings, medial gastrocnemius, soleus, rectus femoris, vastus medialis, and tibialis anterior. EMG signals were amplified (gain 1,000) and band-pass filtered (20–450 Hz) in hardware. All signals were then sampled at 500 Hz via a 12-bit analog-to-digital converter (National Instruments, Austin, TX) on a PC running custom-written LabVIEW program.

Hsu C.J., Kim J., Roth E.J., Rymer W.Z, & Wu M. (2017). Forced Use of the Paretic Leg Induced by a Constraint Force Applied to the Nonparetic Leg in Individuals Poststroke During Walking. Neurorehabilitation and neural repair, 31(12), 1042-1052.

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Respiratory System Mechanics Measurement

Cited 1 time

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Airflow, volume, and airway pressure (P_aw) were recorded with a computer running custom software written in LabVIEW® (National Instruments, Texas, USA; Silva et al., 2013 (link)). All signals were amplified (TAM-D HSE Plugsys Transducers Amplifiers, Module Type 705/2, Harvard Apparatus, MA, USA) and sampled at 200 Hz with a 12-bit analog-to-digital converter (National Instruments, Texas, USA). Respiratory system elastance (E,_RS) and resistance (R,_RS) were calculated based on the equation of motion (Uhlig et al., 2014 (link)):

P_{a w} (t) = R_{R S} • \overset{. \cdot}{V} (t) + E_{R S} • V (t) + P_{0}

, where t is time, V is volume, and P₀ is P_aw at end-expiration. Volume-independent elastance (E1,_RS) and volume-dependent elastance (E2,_RS) as well as the E,_RS non-linearity index (%E2) were calculated cycle-by-cycle as described elsewhere (Carvalho et al., 2013b (link)).

Soluri-Martins A., Moraes L., Santos R.S., Santos C.L., Huhle R., Capelozzi V.L., Pelosi P., Silva P.L., de Abreu M.G, & Rocco P.R. (2017). Variable Ventilation Improved Respiratory System Mechanics and Ameliorated Pulmonary Damage in a Rat Model of Lung Ischemia-Reperfusion. Frontiers in Physiology, 8, 257.

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Measuring Maximal Isometric Force

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During both Pre- and Post-MVCs in all four experimental testing visits, force was detected by the tension applied to the load cell. The force signal was digitized with a 12-bit analog-to-digital converter (National Instruments, Austin, TX) and stored in a personal computer (Dell Optiplex 755, Round Rock, TX) for further analyses. For each force signal, the maximal force output was selected from the highest 1-s portion of the 5-s isometric MVC.

Ye X., Beck T.W., Wages N.P, & Carr J.C. (2018). Sex comparisons of non-local muscle fatigue in human elbow flexors and knee extensors. Journal of Musculoskeletal & Neuronal Interactions, 18(1), 92-99.

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Physiological Signal Acquisition and Amplification

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All parameters were recorded with a computer running custom software written in LabVIEW® (National Instruments; Austin, Texas, USA) (Silva et al., 2013 (link)). All signals were amplified in a three-channel signal conditioner (TAM-D HSE Plugsys Transducers Amplifiers, Module Type 705/2, Harvard Apparatus, Holliston, Massachusetts, USA) and sampled at 200 Hz with a 12-bit analog-to-digital converter (National Instruments; Austin, Texas, USA).

Henriques I., Padilha G.A., Huhle R., Wierzchon C., Miranda P.J., Ramos I.P., Rocha N., Cruz F.F., Santos R.S., de Oliveira M.V., Souza S.A., Goldenberg R.C., Luiz R.R., Pelosi P., de Abreu M.G., Silva P.L, & Rocco P.R. (2016). Comparison between Variable and Conventional Volume-Controlled Ventilation on Cardiorespiratory Parameters in Experimental Emphysema. Frontiers in Physiology, 7, 277.

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Continuous Respiratory Mechanics Monitoring

Cited 1 time

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Airflow, volume, and airway pressure were continuously recorded with a computer running custom software written in LabVIEW (National Instruments; Austin, Texas, USA) (Silva et al., 2013 (link)). All signals were amplified in a three-channel signal conditioner (TAM-D HSE Plugsys Transducers Amplifiers, Module Type 705/2, Harvard Apparatus, Holliston, Massachusetts, USA) and sampled at 1,000 Hz with a 12-bit analog-to-digital converter (National Instruments; Austin, Texas, USA). E and R were calculated offline based on the equation of motion (Uhlig et al., 2014 (link)).

Wierzchon C.G., Padilha G., Rocha N.N., Huhle R., Coelho M.S., Santos C.L., Santos R.S., Samary C.S., Silvino F.R., Pelosi P., Gama de Abreu M., Rocco P.R, & Silva P.L. (2017). Variability in Tidal Volume Affects Lung and Cardiovascular Function Differentially in a Rat Model of Experimental Emphysema. Frontiers in Physiology, 8, 1071.

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Electromyographic Analysis of Gait Mechanics

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Surface electrodes (Delsys DE 2.1, Delsys Inc., Boston, MA) were used to record the electromyograms (EMG) during treadmill walking from 7 muscles on the paretic leg: hip abductor (gluteus medius), medial hamstrings, medial gastrocnemius, soleus, rectus femoris, vastus medialis and tibialis anterior. Electrodes were applied to lightly abraded, degreased skin over the respective muscle belly. EMG signals were amplified (gain 1,000) and band-pass filtered (20–450 Hz) in hardware. All signals were then sampled at 500 Hz via a 12-bit analog-to-digital converter (National Instruments, Austin, TX) on a PC running custom-written LabVIEW program.

Hsu C.J., Kim J., Tang R., Roth E.J., Rymer W.Z, & Wu M. (2017). Applying a pelvic corrective force induces forced use of the paretic leg and improves paretic leg EMG activities of individuals post-stroke during treadmill walking. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 128(10), 1915-1922.

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Respiratory Mechanics Measurement Protocol

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Airflow, airway pressure (P_aw), and P_es were recorded continuously throughout the experiments by a computer running customer-made software written in LabVIEW (National Instruments, USA). V_T was calculated by digital integration of the airflow signal. The total respiratory rate (RR) was calculated from the P_es swings as the frequency per minute of each type of breathing cycle. Peak transpulmonary pressure (Ppeak,_L) was calculated as the difference between tracheal and esophageal pressure. P_0.1 is the esophageal pressure measured 100 ms after the onset of inspiratory effort, and it reflects the neuromuscular drive. All signals were amplified in a three-channel signal conditioner (TAM-DHSE Plugsys Transducers Amplifiers, Module Type 705/2, Harvard Apparatus, Holliston, Massachusetts, USA) and sampled at 200 Hz with a 12-bit analog-to-digital converter (National Instruments; Austin, Texas, USA) [19 (link)]. All mechanical data were computed offline by a routine written in MATLAB (Version R2007a; The Mathworks Inc., USA).

da Cruz D.G., de Magalhães R.F., Padilha G.A., da Silva M.C., Braga C.L., Silva A.R., Gonçalves de Albuquerque C.F., Capelozzi V.L., Samary C.S., Pelosi P., Rocco P.R, & Silva P.L. (2021). Impact of positive biphasic pressure during low and high inspiratory efforts in Pseudomonas aeruginosa-induced pneumonia. PLoS ONE, 16(2), e0246891.

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Respiratory Mechanics Measurement Protocol

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Airflow and airway pressure were continuously recorded throughout the experiments [7 (link), 15 (link), 16 (link)]. V_T, RR, and V′_E were calculated. Respiratory system mechanics were assessed by occluding the airways at end-inspiration for 5 s until a respiratory system plateau pressure (Pplat,_RS) was reached. Respiratory system driving pressure (∆P,_RS) was calculated as the difference between Pplat,_RS (post end-inspiratory pause) and PEEP. All signals were amplified in a four-channel signal conditioner (SC-24, SCIREQ, Montreal, QC, Canada), and sampled at 200 Hz with a 12-bit analog-to-digital converter (National Instruments; Austin, Texas, USA). Mechanical data were computed offline by a routine written in MATLAB (Version R2007a; The Mathworks Inc., Natick, Massachusetts, USA).

Rocha N.N., Samary C.S., Antunes M.A., Oliveira M.V., Hemerly M.R., Santos P.S., Capelozzi V.L., Cruz F.F., Marini J.J., Silva P.L., Pelosi P, & Rocco P.R. (2021). The impact of fluid status and decremental PEEP strategy on cardiac function and lung and kidney damage in mild-moderate experimental acute respiratory distress syndrome. Respiratory Research, 22, 214.

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