The ability to noninvasively assess voluntary muscle effort has wide application in physiologic studies, sports and rehabilitation medicine, as well as movement science. Traditionally, surface electromyography (sEMG) has been used for such assessments, but sEMG has several significant limitations arising from the fact that an estimate of muscle mechanical effort is being obtained from an electrical potential measurement made at the skin surface. As a result, it can be difficult to compare recordings from different muscles on the same person, on the same muscle over a period of days or weeks, or between the same muscle on different individuals. In addition, muscle fatigue studies are difficult as EMG activity tends to increase with increasing fiber recruitment, even though muscle effort is decreasing.
To overcome the limitations associated with using sEMG recordings to evaluate muscle effort, an increasing number of investigators have come to rely upon vibromyography (VMG), or the recording of muscle fiber vibrations, to estimate muscle effort levels. The development of microelectromechanical (MEMS) accelerometers has contributed greatly to this transition as extremely sensitive, very low noise sensors are now available at reasonable cost.
HRV | Frequency Domain Measures You will learn about – Introduction to HRV – Theory and guidelines – Recording great ECG data – Preparing data for analysis – Low Frequency (LF) & High Frequency (HF) measures – Single-epoch spectral HRV analysis – Multi-epoch spectral HRV analysis – Automation with scripting and Workflow – Focus Areas and event-based analysis
BIOPAC provides researchers with a complete range of tools to gather data on heart rate variability (HRV). The following studies demonstrate just some of the ways in which HRV research benefits from the implementation of BIOPAC hardware and software solutions. PTSD and HRV Post-traumatic stress disorder (PTSD) has been associated with dysfunction of the autonomic […]
BIOPAC’s comprehensive Introductory ECG Guide addresses fundamental to advanced concerns to optimize electrocardiography data recording and analysis. Topics include: ECG Complex; Electrical and Mechanical Sequence of a Heartbeat; Systole and Diastole; Configurations for Lead I, Lead II, Lead III, 6-lead ECG, 12-lead ECG, precordial leads; Ventricular Late Potentials (VLPs); ECG Measurement Tools; Automated Analysis Routines for extracting, […]