Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data
2. Materials and Methods
2.2. Data Analysis: EMG Processing and Synergy Extraction and Matching
2.2.2. Synergy Extraction
2.2.3. Synergy Matching
2.3. Data Analysis: Considered Cases
2.3.1. Intra-Session and Inter-Session
2.3.2. Comparison of Synergies from Virtual Electrode Repositioning
2.4. Data Analysis: Outcome Measures
2.4.1. VAF and Number of Extracted Synergies
2.4.2. Similarity of Synergy Spatial Composition
2.4.3. Virtual Electrode Repositioning
- Intra-session virtual electrode repositioning (IntraSessVER)The first step for our analysis was to investigate if a different synergy similarity is detected when slightly repositioning electrodes within the same session. This finding can confirm that electrode repositioning might influence synergy similarity and serves as motivation for the following steps of the analyses.To achieve this, we created a simulated dataset to compare muscle synergy similarity from different virtual electrode positions for the same session. We compared average similarities for all possible repositioning distances (4 mm, 8 mm, 12 mm, and 16 mm). This was repeated for all VAF values. Maximal similarity of synergies (MAX) between any two steps of rotations for each session (and subjects), average similarities (AVRG) between all step pairs, and minimal similarities (MIN) were calculated. MAX values represented, for each subject, the average (computed across 5 sessions) of maximum similarities detected between different electrode positions within each session. To achieve AVRG value similarity, values of all step pairs in each of the sessions were averaged (for each subject). Finally, MIN values represented the average (computed across 5 sessions) of minimum similarities for each subject detected for any combination of electrode positions within same session. In this way, our IntraSessVER dataset was composed of 10 AVRG, 10 MIN, and 10 MAX matching values (one for each subject representing an average of 5 sessions) for each VAF value.
- Inter-session virtual electrode repositioning (InterSessVER)Here, we aimed to assess if repositioning electrodes virtually between sessions can lead to higher similarity between sessions. If this condition was met, a part of the variability in the muscle synergy similarity that existed between sessions can be due to slightly different positions of electrodes. For each possible combination of two sessions, we created a simulated dataset computing the maximum muscle synergy similarity by calculating all combinations of steps for those two sessions. Maximum, minimum, and average similarities between different step pairs (25 combinations) and session pairs (10 combinations) were calculated for all the subjects. MAX values represented the highest similarity that each subject achieved between any two sessions having the option to also shift electrodes between sessions. MIN values reported the minimum value that each subject had between any two sessions. AVRG values were the average of MAX values found for each session pair, calculated for each subject. In this way, our InterSessVER dataset was composed of 10 ARVG, 10 MIN, and 10 MAX matching values (one for each subject) for each VAF value.
- Intra-session without electrode repositioning (IntraSessORIG)The intra-session dataset was created by computing the similarity of the synergies extracted from a different selection of movement repetitions but from the same session (no electrode repositioning). This was the same analysis as already described in Section 2.4.2, but it was repeated using only 8 channels instead of 14 in order to be able to compare the results with that of intra-session using virtual electrode repositioning. Minimum, maximum, and average values of 5 sub-selections of movements from each session were calculated. Then, the average of minimum, maximum, and average values over 5 sessions for each subject were compared with values of the other conditions. MAX values represented for each subject the average (computed across 5 sessions) of maximum similarities detected between movement sub-selections, AVRG values represented the average of average similarities between sub-selections for all sessions, and the MIN average represented minimum similarities of its sub-selections. In this way, our IntraSessORIG dataset was composed of 10 AVRG, 10 MIN, and 10 MAX matching values (one for each subject representing average of 5 sessions) for each VAF value.
- Inter-session without electrode repositioning (InterSessORIG)The intersession dataset was created by computing the similarity of synergies between sessions. The dataset was analogous to the one described in Section 2.4.2 but for only 8 channels instead of 14 and with the original positions of electrodes (no electrode repositioning). MAX values represent the maximum similarity that each subject achieved between any two sessions (with original positions of electrodes), while MIN values report the minimum value that each subject had between any two sessions. AVRG values are the average of all possible session pairs (10 combinations) for each subject. In this way, our InterSessORIG dataset is composed of 10 AVRG, 10 MIN, and 10 MAX matching values (one for each subject) for each VAF value.
- Inter-subject (InterSUBJ)Finally, we considered a fifth condition that we labelled inter-subject (portrayed graphically in Figure 8). The assessment of similarity of spatial synergies between people can enhance the understanding of the generalization of the synergies. The average synergies computed across 5 sessions for each person were calculated (using groups from inter-session matching described in Section 2.4.2) and averaged in the view that they represent individual synergies better than if we chose synergies from one session randomly. These average synergies, representing individual synergies of 10 participants, were then compared in a pairwise manner (45 combinations). MAX values represent the maximum similarity of synergies that each subject had with one of the other subjects (9 combinations), AVRG values are average similarities that each subject had with all other subjects, and MIN values represent the minimum value of similarities each subject had with any of all other subjects. In this way, our InterSUBJ dataset is composed of 10 AVRG, 10 MIN, and 10 MAX matching values (one for each subject representing the average of comparison with 9 other people) for each VAF value.
- Comp#1: to test whether significant differences existed between similarities of synergies extracted from the same sessions (IntraSessORIG) and synergies from different sessions (InterSessORIG) both without virtually repositioning of electrodes. This was analogous to the comparison in Section 2.4.2 but with 8 electrodes instead of 14.
- Comp#2: to test whether a significant difference exists in average values of similarities between intra-session (IntraSessORIG) and intra-session with different steps in virtual electrode repositioning (IntraSessVER). This allowed to show whether higher, lower, or comparable intra-session synergy similarity was achievable when electrodes are virtually repositioned.
- Comp#3: to test whether a significant difference exists between the average value of similarities of sessions with original positions (InterSessORIG) and sessions with the best electrode positioning combination (InterSessVER). This allows us to test whether on average it is possible to get higher inter-session similarity when allowing electrode displacement between sessions. In other words, is it possible that slight electrode repositioning between sessions is one of the factors influencing lower synergy similarity?
- Comp#4: to test whether a significant difference exists between maximal similarities that can be achieved for inter (InterSessVER) and intra-session (IntraSessVER) conditions while allowing electrode repositioning. This allows to test if, by moving electrodes between sessions, for any combination of sessions, it is possible to get similarity as high as with intra-session data.
- Comp#5: to test whether a significant difference exists between synergies of the same subject extracted in different sessions (InterSessORIG) when compared to synergies of other subjects (InterSUBJ). This investigation tests how well muscle synergies generalize between individuals with respect to the average inter-session similarity. The analysis was done in order to assess whether lower inter-session (with respect to intra-session) similarities impose serious concern for multi-session or longitudinal assessments. If inter-subject similarities were lower than inter-session ones, synergies contained subject specific information, but generalization of synergies between subjects may not be very high. On the other hand, if inter-subject similarities were on the same level (or higher) than inter-session, then the synergies generalize well between subjects but it is not possible to distinguish whether synergies are from the same subject but recorded during different sessions or from a completely different subject. This can be a serious point to consider for multi-session assessments.
2.5. Statistical Analysis
3.1. Intra-Session and Inter-Session Variability
3.1.1. VAF and Number of Extracted Synergies
3.1.2. Spatial Muscle Synergy Similarity
3.2. Virtual Electrode Repositioning
Conflicts of Interest
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Pale, U.; Atzori, M.; Müller, H.; Scano, A. Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data. Sensors 2020, 20, 4297. https://doi.org/10.3390/s20154297
Pale U, Atzori M, Müller H, Scano A. Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data. Sensors. 2020; 20(15):4297. https://doi.org/10.3390/s20154297Chicago/Turabian Style
Pale, Una, Manfredo Atzori, Henning Müller, and Alessandro Scano. 2020. "Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data" Sensors 20, no. 15: 4297. https://doi.org/10.3390/s20154297