Showing posts with label biomechanics. Show all posts
Wireless | Influence of Gender on Muscle Activity
Muscle mechanical energy expenditure shows the neuromotor strategies used by the nervous system to analyze human locomotion tasks and is directly related to its efficiency. Kaur, Shilpi, Bhatia, and Joshi investigated the impact of gender on the activity of agonist-antagonist muscles during maximum knee and ankle contraction in males and females. Twenty right leg dominant male and female adult volunteers were recruited in the study. Limb dominance was determined according to which leg the individual chooses and relies on to carry out the activities. Movements of knee and ankle used for the maximum contractions were knee flexion and extension, and ankle plantar flexion and dorsiflexion. EMG Signals were recorded wirelessly from the selected ipsilateral and contralateral muscles of both the dominant and non-dominant lower limbs of all subjects. Recordings used BIOPAC multi-channel Wireless EMG and the collected data was stored using AcqKnowledge software included with the data recording system. Results showed that there is no significant influence of gender on agonist-antagonist muscle energy expenditure during maximum knee contraction. For ankle contractions, gender has significant influence on energy expenditure during maximum ankle dorsiflexion. Researchers found that these results are helpful in understanding gender related differences in the energy expenditure of selected muscles during maximum knee and ankle contractions. The wireless BioNomadix modules used by the researchers permitted free movement for the knee and ankle movements required of the study. The Dynamometry-EMG BioNomadix Pair has matched transmitter and receiver module specifically designed to measure one or both signals. These units interface with the MP150 and data acquisition and AcqKnowledge software, allowing advanced analysis for multiple applications and supporting acquisition of a broad range of signals and measurements. Both channels have extremely high-resolution EMG and Dynamometry waveforms at the receiver’s output. The pair emulates a “wired” connection from the computer to subject, in terms of quality, but with all the benefits of a fully-wireless recording system.
Wireless | Emotion Processing in Schizophrenia
Schizophrenia has long been known to be a very complicated and poorly understood cognitive disorder. To attempt to understand the differences in emotional processing in schizophrenic patients, psychologists use physiological parameters to quantify psychological activity. Researchers Peterman et al. performed a study in which Galvanic Skin Response (GSR or EDA) and Facial Electromyography (fEMG) were recorded in schizophrenic and control subjects in response to social stimuli to assess the differences in adaptive emotional response. To measure these signals, they used wireless BIOPAC BioNomadix amplifiers, one for GSR (BN-PPGED) and two for fEMG (BN-EMG2). The participants were asked to view a block of images of the same category (e.g., social positive, non-social negative, etc.), then select a positivity response (valence rating) as to how they felt about the images. Subjects viewed several blocks of images to evoke differing responses. The self-reported valence ratings were paired to physiological data acquired with wireless BioNomadix transmitters. The GSR and fEMG were collected with an MP150 data acquisition system, and the data was analyzed with AcqKnowledge software. Researchers found that the Schizophrenic subjects responded similarly to the controls in the valence ratings, but their GSR and fEMG data diverged significantly. The Schizophrenic subjects showed a stronger overall GSR response to the images; however they did not show an effect by the sociality of the pictures. The fEMG response was also greater overall in the Schizophrenic group, but also did not vary by sociality. The results provide physiological background to the disrupted self-awareness of emotion processing in Schizophrenics. The complexity of emotion processing in cognitive disorders continues to elude us and to pave new avenues for scientific study. Along with the BioNomadix modules used in the study, BIOPAC Systems offers several wireless, wearable physiological data acquisition and analysis systems for psychophysiological research.
Wireless, Wearable | Quality of Life Technologies
There is a major concern growing in the medical community that the ratio of health workers to population size is decreasing. This means that the number of available doctors and medical professionals is starting to become too small to handle the number of people needing medical help. Technologies are therefore being created to help bridge the gap that is being created. These “Quality of Life Technologies” (QoLTs) have been developed to help monitor the health of people. While these technologies have been able to provide physiological support to individuals, the same could not be said for mental symptoms. If QoLTs could move into the realm of psychology and self-therapy, they could help improve the mood and quality of life for patients. A group of researchers from the Polytechnic University of Bucharest and the University of Lincoln recently published a paper that presents a machine learning approach for stress detection using wearable physiological amplifiers. To induce stress in participants, the researchers had them perform both a public speaking and cognitive task, which according to previous research these tasks caused the highest increase in measurable signals.
For their experimental setup, they used a BIOPAC BioNomadix BN-PPGED wireless transducer, hooked up to an MP150 data acquisition system, to record both EDA and PPG signals. They then used AcqKnowledge 4 software to extract both the PPG autocorrelation signal and Heart Rate Variability (HRV). Their results provided accurate stress detection in individuals. Their analysis marks a good starting point toward real-time mood detection, which could lead to people improving their quality of life. One way they could improve their experimental setup however, would be to use the BioNomadix Logger. This device allows for up to 24 hours of high quality data logging allowing the researchers to analyze a subject’s data from when they encountered stressful situations outside the lab.
Biomechanics Transducers | Data Acquisition
Biomechanics
data can include measures of force and motion of body position, posture, and
joint movement over a wide range of static and dynamic conditions. Biomechanics
measurements are meaningful for a wide variety of research applications, such as
biomedical engineering, exercise physiology, sports training or rehab, and
ergonomics (for characteristics of a specific work activity or environment).
Biomechanics transducers include goniometers, torsiometers, and
accelerometers. Transducers are unobtrusive and lightweight, and can be worn
comfortably and undetected under clothing or attached to external
equipment—leaving the subject to move freely in the normal
environment.
Biomechanics transducers connect directly to the BIOPAC Acquisition Unit as part of an MP or BSL System. For a more complete physiological analysis, additional signals can be recorded (e.g., EMG, respiration, heart rate) and video data can be tightly-synchronized for a clear and detailed view of the biomechanics of a movement with the subject’s physiological data.
Goniometers incorporate gauge elements that measure bending strain along or around a particular axis and transform angular position into a proportional electrical signal. The gauge mechanism allows for accurate measurement of polycentric joints. As the joint moves through a determined angle, the relative linear distance between the two mounting positions will change. A telescopic endblock prevents the measuring element from becoming over-stretched or buckled as the limb moves. The bending strain is proportional to the sum total angular shift along the axis. Because the bending force is extremely small, the output signal is uniquely a proportional function of the angular shift.
Twin-axis goniometers measure rotation about two orthogonal planes
simultaneously to record limb angular movement, such as adequate bending in the
elbows or knees, unsafe rounding in the lower spine, wrist or ankle
flexion/extension, abduction/adduction, radial/ulnar deviations, etc.
Single-axis goniometers measure the angle in one plane only and are used to
record digit joint movement of fingers, thumb or
toes.
Torsiometers measure rotation about a single axis (e.g., forearm pronation/supination) to record angular twisting (as opposed to bending) of the torso, spine or neck.
Tri-Axial Accelerometers are high level output transducers that provide three outputs to measure acceleration along the X-, Y- and Z-axes simultaneously. To reliably record head tilt, place an accelerometer on the head. To measure accelerations when performing slow movements, such as walking and hand tremor, ±5 G accelerometers are optimal; ±50 G are more suitable for quick movements, such as swinging a tennis racket.
For applications where quick or rapid movements are involved, fit a “sock” bandage over the whole sensor and interconnect lead. For accurate results from long recordings, use double-sided adhesive between the endblocks and skin, and place single-sided adhesive tape over the top of the endblocks. No tape should come into contact with the spring. The connection lead should also be taped down near the sensor element.
Biomechanics transducers connect directly to the BIOPAC Acquisition Unit as part of an MP or BSL System. For a more complete physiological analysis, additional signals can be recorded (e.g., EMG, respiration, heart rate) and video data can be tightly-synchronized for a clear and detailed view of the biomechanics of a movement with the subject’s physiological data.
Goniometers incorporate gauge elements that measure bending strain along or around a particular axis and transform angular position into a proportional electrical signal. The gauge mechanism allows for accurate measurement of polycentric joints. As the joint moves through a determined angle, the relative linear distance between the two mounting positions will change. A telescopic endblock prevents the measuring element from becoming over-stretched or buckled as the limb moves. The bending strain is proportional to the sum total angular shift along the axis. Because the bending force is extremely small, the output signal is uniquely a proportional function of the angular shift.
Torsiometers measure rotation about a single axis (e.g., forearm pronation/supination) to record angular twisting (as opposed to bending) of the torso, spine or neck.
Tri-Axial Accelerometers are high level output transducers that provide three outputs to measure acceleration along the X-, Y- and Z-axes simultaneously. To reliably record head tilt, place an accelerometer on the head. To measure accelerations when performing slow movements, such as walking and hand tremor, ±5 G accelerometers are optimal; ±50 G are more suitable for quick movements, such as swinging a tennis racket.
For applications where quick or rapid movements are involved, fit a “sock” bandage over the whole sensor and interconnect lead. For accurate results from long recordings, use double-sided adhesive between the endblocks and skin, and place single-sided adhesive tape over the top of the endblocks. No tape should come into contact with the spring. The connection lead should also be taped down near the sensor element.
EMG Analysis | Biomechanics
Biomechanics
research has never been easier thanks to powerful new data acquisition and
analysis tools. Perform real-time calculations and post-data acquisition
analysis on a variety of biomechanical and physiological data.
Simultaneously
acquire up to 16 channels of biomechanics and/or gait-specific data. An example
setup could incorporate two channels of heel/toe
strike timing, ten channels of EMG signals, and
four channels of goniometry data — however combinations are virtually endless.
Record sit-and-reach tests, range of motion evaluations, muscle balance
assessments and more.
Real-time
event markers allow researchers to log important events in the data and also
include comments that can be written during or post acquisition.
After
recording, choose an automated
analysis package to interpret and score the biomechanics data. For example,
automated EMG
analysis allows for a variety of automated functions including deriving
integrated EMG, root mean square (RMS) EMG, locating muscle activation, full
frequency and power analysis, and much more.