Influence of Gender on Accelerometry Patterns

Abstract

Purpose Human movement is considered one of the important factors for maintaining an independent life. Besides, the way a person walks is considered a personal identification trait and may be able to distinguish individuals with the same pathological condition, with the same range, of the same gender and the same ethnicity (Connor; Ross, 2018; Yu et al., 2009). Although the use of the accelerometer is becoming increasingly common in the health area, a standard has not yet been created on which frequency patterns are ideal to discriminate individuals according to gender, especially when they are out of clinical settings, carrying out their activities of daily living. The aim of this study was to identify which accelerometry characteristics extracted from the use of a triaxial accelerometer during 7 days of activities of daily living are associated with female and male gender. Method A cross-sectional study was conducted based on the database of the first wave of the Epidemiological Study of Movement (EPIMOV) cohort. Data from 1080 participants aged from 18 years were evaluated, the participants included in the study did not have health conditions that could interfere with the pattern of the walking pattern or postural control, such as diseases of the central nervous system (stroke, Parkinson's), peripheral neuromuscular disorder (sclerosis), neurocognitive decline or amputation and/or use of a lower limb prosthesis or other device that modifies the gait pattern, presence of claudication, among others. Participants whose accelerometry data showed errors, such as incomplete or inconsistent data, were excluded. Features of entropy (PSE), frequency (PSPF1, PSPF2, PSPF3), amplitude (PSP1, PSP2, PSP3), harmonic components of the gait (WPSP), and Counts were extracted from the accelerometer (ActiGraph GT3X +, MTI, Pensacola, FL) signal obtained from 7 days of daily life activities. These accelerometry variables have previously been successfully explored to identify older adult fallers (Ponti et al., 2017; Bet; Castro; Ponti, 2021). Two-way analysis of variance was employed to compare the variables according to the groups. Results and Discussion The sample consisted mostly of female participants between 18-39 years old (n=254), 40-59 years old (n=271) and ≥ 60 years old (n=109). The table below describes the primary outcomes with the continuous variables of accelerometry of all study participants. The entropy features (PSE) and the amplitude features (PSP1, PSP2 and PSP3) showed a significant difference between the female and male genders (See Table 1). The results demonstrated the interference of gender in movement patterns. Most articles published on the topic do not consider gender, so it would be interesting in future studies for movement patterns to be adjusted according to the gender of the participants.