Bagnoli system

Manufactured by Delsys

Sourced in United States

The Bagnoli system is a lab equipment product designed for electromyography (EMG) signal acquisition and analysis. It provides a hardware interface and software tools for recording and processing EMG data. The core function of the Bagnoli system is to facilitate the measurement and investigation of muscle activity.

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Lab products found in correlation

Visual3d, by C-Motion (2 mentions) Oqus 3, by Qualisys (2 mentions) Usb 6363 bnc, by National Instruments (1 mentions) Oqus system, by Qualisys (1 mentions)

Spelling variants of this product

Bagnoli (17 citations) Bagnoli 8 EMG System (13 citations) Bagnoli EMG system (10 citations) Bagnoli 16-channel EMG system (6 citations) Bagnoli-2 EMG system (4 citations) Bagnoli sEMG system (3 citations) Bagnoli desktop EMG system (3 citations) Bagnoli-4 EMG System (3 citations) Bagnoli Desktop system (2 citations) Bagnoli-8 system (2 citations)

9 protocols using bagnoli system

Kinematic and EMG Analysis of Dominant Limb

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The dominant (preferred kicking) limb was selected for data collection. Prior to electrode placement, the skin was shaved abraded and cleaned with isopropyl alcohol. Parallel-bar EMG Sensors (DE-2.1, DELSYS, USA) were then placed over the BF and ST in accordance to SENIAM guidelines (Hermens et al. 2000). EMG signals were amplified (1 k gain) via a Delsys Bagnoli system (Delsys Inc. Boston, MA, USA) with a bandwidth of 20–450 Hz. The common mode rejection rate and input impedance were -92 dB and >10¹⁵Ω, respectively. Data was collected at 1000 Hz synchronously with the kinematic data.
Lower extremity planar kinematics was monitored using a 10-camera retroreflective system at 200 Hz (Oqus 3, Qualisys Gothenburg, Sweden). Four retroreflective soft markers (19 mm) were placed over the lateral malleolus, lateral knee joint, greater trochanter and acromion process of the dominant limb. Following tracking, kinematic and sEMG data were exported for analysis to Visual 3D (C-Motion Inc. USA).

Monajati A., Larumbe-Zabala E., Goss-Sampson M, & Naclerio F. (2017). Analysis of the Hamstring Muscle Activation During two Injury Prevention Exercises. Journal of Human Kinetics, 60, 29-37.

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Arm Force Control via EMG Signals

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Subjects sat on a chair facing a computer screen and held a handle attached to a force sensor centered at the body midline. The height of the seat was adjusted so that the sensor and the arm lay on a horizontal plane. The arm’s weight was supported by a two-link elbow support, and the wrist was constrained by a splint. Based on previous studies (Berger et al., 2013 (link)), surface EMG signals from 10 shoulder and elbow muscles (i.e., trapezius, posterior deltoid, middle deltoid, anterior deltoid, pectoralis major, triceps brachii long head, biceps long head, triceps brachii lateral head, brachioradialis, and pronator teres) were measured using bipolar electrodes (Bagnoli system; Delsys). The arm end-point force was measured with a 6-axis force sensor (DynPick WEF-6A200; Wacoh-tech). Raw EMG and force data were sampled at 2,000 Hz using an analog-to-digital converter (USB-6363 BNC; National Instruments) and processed and analyzed using Matlab 2020. Filtered end-point force data were projected on a 30-inch LCD screen as a visual feedback cursor, so that subjects could control the cursor position according to the experiment instructions.

Cho W., Barradas V.R., Schweighofer N, & Koike Y. (2022). Design of an Isometric End-Point Force Control Task for Electromyography Normalization and Muscle Synergy Extraction From the Upper Limb Without Maximum Voluntary Contraction. Frontiers in Human Neuroscience, 16, 805452.

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Limb Kinematics and Muscle Activity

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The dominant (preferred kicking) limb was selected for data collection. Prior to electrode placement, the skin was shaved, abraded and cleaned with isopropyl alcohol. Parallel-bar EMG Sensors (DE-2.1, DELSYS, USA) were then placed over the BF, ST, VL and VM in accordance with SENIAM guidelines (Hermens et al., 2000 (link)). EMG signals were amplified (1 k gain) via a Delsys Bagnoli system (Delsys Inc. Boston, MA, USA) with a band-width of 20–450 Hz. A common mode rejection rate and input impedance were -92 dB and >10¹⁵Ω, respectively. Data was collected at 1000 Hz synchronously with the kinematic data.
Lower extremity planar kinematics was monitored using a 10-camera retroreflective system at 200 Hz (Oqus 3, Qualisys Gothenburg, Sweden). Four retroreflective soft markers (19 mm) were placed over the lateral malleolus, lateral knee joint, greater trochanter and acromion process of the dominant limb. Following tracking, kinematic and sEMG data were exported for analysis in Visual 3D (C-Motion Inc. USA).

Monajati A., Larumbe-Zabala E., Goss-Sampson M, & Naclerio F. (2019). Surface Electromyography Analysis of Three Squat Exercises. Journal of Human Kinetics, 67, 73-83.

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Facial Muscle Activation Measurement

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Bilateral activation of the orbicularis oris muscles was measured using a surface electromyography (sEMG) system (Delsys two-channel Bagnoli system) in combination with an external sound card (M-Audio Fast Track PRO. The Delsys Bagnoli system band-pass filtered sEMG signals prior to acquisition with corner frequencies of 20 Hz and 450 Hz. The bilateral orbicularis oris muscles were chosen to provide high signal-to-noise ratios for control of the interface. Before placing the sEMG electrodes on the subject, the skin was prepared by swabbing with alcohol wipes and exfoliating with tape (peeling) according to previous methods (Stepp, 2012 (link)). Double differential electrodes were cleaned, prepared with double-sided adhesive interfaces, and placed over the left and right orbicularis oris muscles. A ground electrode (Dermatrode) was placed on the acromion process of each subject. Each channel was amplified by a gain of 1000 prior to acquisition. The sEMG signals were then digitized at 44.1 kHz.

Hands G.L., Larson E, & Stepp C.E. (2014). Effects of augmentative visual training on audio-motor mapping. Human movement science, 35, 145-155.

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Kinematic and sEMG Data Collection

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Kinematic data were recorded using a VICON Bonita system (VICON Motion Systems Ltd., Oxford, UK) at a rate of 120 Hz. Fifteen reflective markers were placed on the participants’ shoulders and clavicle, as well as on the elbow, wrist, metacarpals, index finger and thumb of the dominant arm and hand. sEMG data were collected with a DELSYS Bagnoli system (DELSYS Inc., Natick, MA, USA) at 960 Hz from seven double-differential, dry-contact sEMG sensors integrated into a fabric band. The raw data were processed with a 6th-order Butterworth filter (10–450 Hz), followed by a 60-Hz notch filter to remove any noise from surrounding electrical equipment. Data were then mean-subtracted and rectified.

Siu H.C., Shah J.A, & Stirling L.A. (2016). Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography. Sensors (Basel, Switzerland), 16(11), 1782.

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Neck Muscle Surface EMG Recordings

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One single differential sEMG electrode was placed on the anterior neck surface, positioned approximately 2.5 cm lateral to the neck midline and with the superior aspect of the sensor approximately 1 cm from the submental surface. This electrode was expected to detect activity from the thyrohyoid, sternohyoid, and possibly omohyoid muscles. A second electrode placed on the submental surface was intended to measure the combined activations of the digastric, mylohyoid, and geniohyoid muscles. Both electrodes may have also recorded activity from the platysma muscle, which extends from the jaw to the fascia of the pectoralis muscles near the clavicle and contributes to recordings from the neck surface.
The skin surface was prepared with alcohol and exfoliation (Stepp, 2012 (link)). A ground electrode was placed on the superior aspect of the participant’s left shoulder. The sEMG signals were pre-amplified (1000×) and band-pass filtered from 20 Hz to 450 Hz, using a Delsys™ Bagnoli system (Boston, MA) and sampled at 8000 Hz.

Malloy J.R., Valentin J.C., Hands G.L., Stevens C.A., Langmore S.E., Noordzij J.P, & Stepp C.E. (2014). Visuomotor control of neck surface electromyography in Parkinson’s disease. NeuroRehabilitation, 35(4), 795-803.

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Multimodal Assessment of Gait Biomechanics

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Data were collected from three trials under each condition. Force data were collected through three AMTI plates, two platforms side by side and a third platform solely to detect heel-swing contact (Advanced Mechanical Technology, Inc, Water-town, MA).
For movement data, a lO-camera Oqus System (Qualisys Medical AM, Gothenburg, Sweden) was used. Calibration of the Oqus System was performed before each data collection session. Electromyography (EMG) data were collected from the tibialis anterior (TA) and medial GS muscles on the left and right side using 4 DE-2.1 single differential surface EMG sensors with a fixed 10 mm electrode distance placed over the belly of the muscle. These were recorded through a Bagnoli system with preamplified gain of 1000 (Delsys, Inc, Boston, MA). Alcohol wipes were used to clean and lightly abrade the skin surface prior to attachment of the electrodes. The EMG signals were examined visually for any obvious data quality issues or cross talk prior to commencing data collection. Force and EMG data were attained using a 16-bit analog-to-digital converter at 2000Hz.

Egerton C.J., McCandless P., Evans B., Janssen J, & Richards J.D. (2015). Laserlight visual cueing device for freezing of gait in Parkinson's disease: a case study of the biomechanics involved. Physiotherapy theory and practice, 31(7).

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Electromyography of Trunk and Leg Muscles

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Electromyography (EMG) was performed as described previously [34 ]. In brief, EMG was collected using a 16-channel Delsys Bagnoli system (Delsys Inc, Boston, MA, USA; bandwidth 20-450 Hz); the bar leads were modified with clip leads to allow attachment to Ag-Ag Cl surface electrodes over the erector spinae (ERS) at the L2 and L4 level aligned between the posterior superior iliac spine and the lateral border of the muscle at the 12th rib, gluteus maximus midway between the greater trochanter and the posterior superior iliac spine, and long head of the biceps femoris (BF) midway between the fibular head and the ischial tuberosity. The raw surface EMG data were amplified (1k) and A/D converted with 16-bit resolution, sampled at 1000 Hz, and averaged across sides for each muscle.

Applegate M.E., France C.R., Russ D.W., Leitkam S.T, & Thomas J.S. (2018). Determining Physiological and Psychological Predictors of Time to Task Failure on a Virtual Reality Sørensen Test in Participants With and Without Recurrent Low Back Pain: Exploratory Study. JMIR Serious Games, 6(3), e10522.

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Surface EMG of Hand Muscles

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Bipolar surface EMG were collected using a Delsys Bagnoli system (Delsys, Natick, MA) from the first dorsal interosseous (FDI) and abductor pollicis brevis (APB). Data were filtered between 20 and 450 Hz, amplified by 1000, and then sampled at a 2048 Hz. The reference electrode for the recordings was placed on the olecranon of the right arm. Recording locations were identified by palpating the muscle during force production in the direction of mechanical action for each muscle.

Reyes A., Laine C.M., Kutch J.J, & Valero-Cuevas F.J. (2017). Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies. Frontiers in Computational Neuroscience, 11, 17.

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