Machine learning-based detection of acute psychosocial stress from body posture and movements.

Investigating acute stress responses is crucial to understanding the underlying mechanisms of stress. Current stress assessment methods include self-reports that can be biased and biomarkers that are often based on complex laboratory procedures. A promising additional modality for stress assessment might be the observation of body movements, which are affected by negative emotions and threatening situations. In this paper, we investigated the relationship between acute psychosocial stress induction and body posture and movements. We collected motion data from N = 59 individuals over two studies (Pilot Study: N = 20, Main Study: N = 39) using inertial measurement unit (IMU)-based motion capture suits. In both studies, individuals underwent the Trier Social Stress Test (TSST) and a stress-free control condition (friendly-TSST; f-TSST) in randomized order. Our results show that acute stress induction leads to a reproducible freezing behavior, characterized by less overall motion as well as more and longer periods of no movement. Based on these data, we trained machine learning pipelines to detect acute stress solely from movement information, achieving an accuracy of 75.0 ± 17.7 % (Pilot Study) and 73.4 ± 7.7 % (Main Study). This, for the first time, suggests that body posture and movements can be used to detect whether individuals are exposed to acute psychosocial stress. While more studies are needed to further validate our approach, we are convinced that motion information can be a valuable extension to the existing biomarkers and can help to obtain a more holistic picture of the human stress response. Our work is the first to systematically explore the use of full-body body posture and movement to gain novel insights into the human stress response and its effects on the body and mind.

Differences in acute stress responses depending on first or second language in a Hispanic-American sample.

Using a second language is a daily experience for many people today, among them many migrants. To determine whether speaking a second language induces a stronger cortisol or alpha-amylase (sAA) response than first language, we tested a Hispanic-American sample in two Trier Social Stress Test (TSST) conditions: First (Spanish) and second (German) language. Thirty-two participants (64.5% female) between the age of 19 and 53 years (mean = 30.68) from Latin America were tested (15 in Spanish, 17 in German). Participants were randomized to a German or Spanish version of the TSST, gave six saliva samples and completed questionnaires on perceived threat and stress, positive and negative affect as well as state-anxiety. A significantly higher stress response was found in the German condition for salivary cortisol, but not for sAA. Self-report showed significantly higher perceived threat and negative affect after the TSST for the German compared to the first language condition. Speaking a second compared to first language in a challenging situation appeared to be more stressful and threatening for participants. Further, reported increases in state-anxiety appeared to be higher in the German condition, even though group differences did not reach significance. A more detailed investigation of underlying, stress inducing mechanisms should be considered in future studies as well as associations with language proficiency and improvements over time.