What Early Scientific Studies Led to the Development of Computer Voice Stress Analysis?

What Early Scientific Studies Led to the Development of Computer Voice Stress Analysis?

The scientific research behind the Computer Voice Stress Analyzer (CVSA) goes back over sixty years. One of the earliest studies, published in 1957 by O.C.J. Lippold, J.W.T. Redfearn, and J. Vuco of the Department of Physiology at University College London, was one of the first to suggest that stress could affect the movements of voluntary muscles, which includes those in the vocal tract. The findings in their paper, “The Rhythmical Activity of Groups of Motor Units in the Voluntary Contraction of Muscle,” served as a basis for much of the later research that paved the way for the development of modern CVSA technology.

In this study, Lippold, Redfearn, and Vuco set out to better understand what they called the “rhythmic tendency of muscle activity.” Before the experiment, scientists had measured mechanical oscillations in voluntary muscles (sometimes called physiological tremor), which occurred at a frequency of about 9 to 10 cycles per second. They hypothesized that these oscillations would match up with action potentials in muscle cells. If their hypothesis was correct, it would suggest that the mechanical movements of voluntary muscles are directly tied to action potentials in muscle cells and that they can, therefore, be affected by the same factors, including physical and psychological stress.

Experimental Measurements of Action Potentials in Muscle Cells

In order to understand this experiment, it is helpful to consider what action potentials are and how they affect voluntary muscle contractions. When a muscle cell is at rest, there is a high concentration of negatively charged chloride ions inside the cell and a high concentration of  potassium ions outside the cell, so the muscle cell has a negative polarization. When the muscle cell is stimulated, the polarization is momentarily reversed, leading to a muscle contraction known as an action potential. Within moments, repolarization occurs and the cell returns to the resting state.

In their experiment, Lippold, Redfearn, and Vuco visualized action potentials on electrical recordings and compared them to recordings of mechanical oscillations. In a series of 57 experiments on 37 subjects, they observed the action potentials in calf muscles both at rest and under stress. The general setup of the experiment had the subject stand in a tub of water with an electrode attached to one of their calf muscles. The electrode made it possible to record the action potentials, which the scientists could then evaluate visually.

On most of the recordings, the scientists observed that action potentials were occurring in the muscle cells at a certain frequency. The resulting charts were similar to what you see when watching a heart monitor: a flat line indicating rest, followed by a burst of activity which quickly returns to a flat line. As the scientists had expected, these action potential bursts were occurring at a frequency of about 8 to 10 cycles per second—right in line with the previously measured frequency of physiological tremor.

Although this association did not provide a direct mechanistic explanation for the connection between electrical and mechanical activity, it allowed scientists to make the case that action potentials underpin physiological tremor—that is, action potentials are the underlying phenomenon, and physiological tremor is the mechanical result.   

Exploring the Effects of Stress on Physiological Tremor

Although Lippold, Redfearn, and Vuco did not measure the effects of psychological stress on action potential bursts and physiological tremor, they did introduce sources of physical stress. For instance, to assess the effect of fatigue, they had the subjects contract their calf muscles for four minutes at 75 percent of their maximum strength. Not only did this increase the frequency of action potential bursts and physiological tremor during and after the experiment, but it also increased the degree to which these two phenomenons were associated. Similarly, putting pressure on the subject’s Achilles tendon or having them lean forward increased the mechanical and electrical frequencies to about 10 to 15 cycles per second. This shows how even small amounts of physical stress can affect activity in muscle cells.

The authors also explored the effects of cooling on mechanical and electrical frequencies by having the subjects stand in tubs of cold water. This led to a reduction in frequency from 9 cycles per second to 6 cycles per second. The amplitude of oscillations was also reduced, and the action potential bursts were less well-defined on the recordings, but the mechanical and electrical oscillations were still relatively synchronized. Therefore, this experiment served as further proof of the connection between action potential and electrical/mechanical signals.

Implications for Voice Stress Analysis

The most important takeaway from this experiment is that electrical signaling in muscle cells serves as the basis for physiological tremor. Therefore, the factors that affect the frequency of action potentials in muscle cells also affect the mechanical movements of muscles.

It is these changes that are measured by today’s CVSA technology. Of course, the voluntary muscles being monitored are those involved in voice production, not calf muscles, but they work the same way. Physiological tremor is directly affected by the action potentials generated by the autonomic nervous system, and the activity of the autonomic nervous system changes in response to stress. These changes allow law enforcement officials to detect moments of high stress which may indicate deception.  

Ultimately, this study not only provided insight into how voluntary muscles work, but it also served as a foundation for further research and development efforts that eventually led to the CVSA. Today, it stands as a landmark study that illustrates the scientific underpinnings of CVSA and the long history of high-quality research in the field.
  

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