Embodimetrics: A Principal Component Analysis Study of the Combined Assessment of Cardiac, Cognitive and Mobility Parameters.

There is a growing body of literature investigating the relationship between the frequency domain analysis of heart rate variability (HRV) and cognitive Stroop task performance. We proposed a combined assessment integrating trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac, and motor variables using principal component analysis (PCA). Additionally, we assessed changes in the relationships among these variables after a two-month intervention aimed at improving the perception-action link. At baseline, PCA correctly identified three components: one related to cardiac variables, one to trunk motion, and one to Stroop task performance. After the intervention, only two components were found, with trunk symmetry and range of motion, accuracy, time to complete the Stroop task, and low-frequency heart rate variability aggregated into a single component using PCA. Artificial neural network analysis confirmed the effects of both HRV and motor behavior on cognitive Stroop task performance. This analysis suggested that this protocol was effective in investigating embodied cognition, and we defined this approach as "embodimetrics".

Ambulatory assessment of shoulder abduction strength curve using a single wearable inertial sensor.

The aim of the present article was to assess the reliability of strength curves as determined from tridimensional linear accelerations and angular velocities measured by a single inertial measurement unit (IMU) fixed on the upper arm during a shoulder abduction movement performed holding a 1 kg dumbbell in the hand. Within-subject repeatability of the task was assessed on 45 subjects performing four trials consisting of one maximal shoulder abduction-adduction movement. Intraclass correlation coefficient (ICC) was computed on the average movement angular velocity (VEL) and range of movement (ROM) across the four trials. Within-subject repeatability of torque curves was assessed in terms of waveform similarities by computing the coefficient of multiple determination (CMD). Accuracy of the estimated ROM was assessed using an isokinetic dynamometer. High ICC values of ROM (0.955) and VEL (0.970) indicated a high within-subject repeatability of the task. A high waveform similarity of torque curves was also found between trials (CMD = 0.867). Accuracy with respect to isokinetic dynamometer in estimating ROM was always <1 degree (p = 0.37). This study showed the effectiveness of using a single wearable IMU for the assessment of strength curve during isoinertial movements in a way that complies with the needs of clinicians in an ambulatory setting.

Non-invasive assessment of superficial soft tissue local displacements during movement: a feasibility study.

In the movement analysts community, the assessment of the displacement of skin photogrammetric markers relative to the underlying bone (soft tissue displacement, STD) is considered to be a priority. The aim of this study is to present a non-invasive method that allows for the characterization of STD for any marker location, subject, and motor task. In particular, this method provides an estimate of the STD vector in a bone-embedded frame. The body segment under analysis is endowed with the largest possible number of skin markers located over all areas of interest. Any given STD vector is observed from all the marker cluster frames that can be built by suitably combining all the available markers. A subset of the latter frames is identified that is made of frames endowed with uncorrelated local movements. The estimate of a given STD vector is determined through the coherent average of the vectors reconstructed using the above-mentioned independent frames. This estimate is affected by a 180 degrees phase indeterminacy. The proposed method and the underlying hypotheses were validated using markers located on the thighs of two female subjects treated for a total knee replacement. The relevant STD estimates, STDm, were compared with those directly observed using photogrammetry combined with 2D fluoroscopic projections and the prosthesis CAD model (STDf). Recordings were made while the volunteers performed step up/down motor tasks. The root mean square value of STDm was found in the range 2.5-23.0 mm and was consistent with the RMS values of STDf and with other results reported in the literature and obtained in similarly unconstrained conditions. Moreover, STDm and STDf showed a pattern similarity measured by a correlation coefficient equal to 0.83 (+/-0.13) and by a normalised root mean square distance equal to 27% (+/-16%). The described estimate of the STD pattern and magnitude, even with the above-mentioned indeterminacies, constitutes valuable information when aiming at optimal marker placement and is an indispensable prerequisite for bone pose estimator design and assessment.