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The impact of the stimulation frequency on closed-loop control with electrotactile feedback.

Paredes LP, Dosen S, Rattay F, Graimann B, Farina D - J Neuroeng Rehabil (2015)

Bottom Line: The quality of tracking was assessed using the Squared Pearson Correlation Coefficient (SPCC), the Normalized Root Mean Square Tracking Error (NRMSTE) and the time delay between the reference and generated trajectories (TDIO).The results demonstrated that FSTIM was more important for the control performance than FTE.The outcome of this study can facilitate the selection of optimal system parameters for somatosensory feedback in upper limb prostheses.

View Article: PubMed Central - PubMed

Affiliation: Laboratorio di Cinematica e Robotica, Fondazione Ospedale San Camillo - I.R.C.C.S., Lido di Venezia, Italy. lparede@gwdg.de.

ABSTRACT

Background: Electrocutaneous stimulation can restore the missing sensory information to prosthetic users. In electrotactile feedback, the information about the prosthesis state is transmitted in the form of pulse trains. The stimulation frequency is an important parameter since it influences the data transmission rate over the feedback channel as well as the form of the elicited tactile sensations.

Methods: We evaluated the influence of the stimulation frequency on the subject's ability to utilize the feedback information during electrotactile closed-loop control. Ten healthy subjects performed a real-time compensatory tracking (standard test bench) of sinusoids and pseudorandom signals using either visual feedback (benchmark) or electrocutaneous feedback in seven conditions characterized by different combinations of the stimulation frequency (FSTIM) and tracking error sampling rate (FTE). The tracking error was transmitted using two concentric electrodes placed on the forearm. The quality of tracking was assessed using the Squared Pearson Correlation Coefficient (SPCC), the Normalized Root Mean Square Tracking Error (NRMSTE) and the time delay between the reference and generated trajectories (TDIO).

Results: The results demonstrated that FSTIM was more important for the control performance than FTE. The quality of tracking deteriorated with a decrease in the stimulation frequency, SPCC and NRMSTE (mean) were 87.5% and 9.4% in the condition 100/100 (FTE/FSTIM), respectively, and deteriorated to 61.1% and 15.3% in 5/5, respectively, while the TDIO increased from 359.8 ms in 100/100 to 1009 ms in 5/5. However, the performance recovered when the tracking error sampled at a low rate was delivered using a high stimulation frequency (SPCC = 83.6%, NRMSTE = 10.3%, TDIO = 415.6 ms, in 5/100).

Conclusions: The likely reason for the performance decrease and recovery was that the stimulation frequency critically influenced the tactile perception quality and thereby the effective rate of information transfer through the feedback channel. The outcome of this study can facilitate the selection of optimal system parameters for somatosensory feedback in upper limb prostheses. The results imply that the feedback variables (e.g., grasping force) should be transmitted at relatively high frequencies of stimulation (>25 Hz), but that they can be sampled at much lower rates (e.g., 5 Hz).

No MeSH data available.


Related in: MedlinePlus

Quality of tracking averaged over all subjects and trials in each condition (VF and FTE/FSTIM). Square Pearson Correlation Coefficient, SPCC (a) and Normalized Root Mean Square Tracking Error, NRMSTE (b). In the VF condition, the performance was significantly higher than in the electrotactile feedback conditions. The closed-loop control performance first steadily worsened (decreasing SPCC, increasing NRMSTE) with the decrease of the stimulation frequency and tracking error sampling rate, but then it almost completely recovered when the low rate tracking error information was delivered using high stimulation frequencies (5/50 and 5/100). Note the abrupt performance drop in SPCC after the condition 25/25. The asterisks and horizontal bars denote statistically significant difference between the pairs of conditions. Only a black asterisk above a condition indicates that in this condition the SPCC/NRMSTE was statistically different from all other conditions. The grey asterisks in NRMSTE denote that the conditions 10/10 and 5/5 differed significantly from all other conditions, but not with respect to each other.
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Fig6: Quality of tracking averaged over all subjects and trials in each condition (VF and FTE/FSTIM). Square Pearson Correlation Coefficient, SPCC (a) and Normalized Root Mean Square Tracking Error, NRMSTE (b). In the VF condition, the performance was significantly higher than in the electrotactile feedback conditions. The closed-loop control performance first steadily worsened (decreasing SPCC, increasing NRMSTE) with the decrease of the stimulation frequency and tracking error sampling rate, but then it almost completely recovered when the low rate tracking error information was delivered using high stimulation frequencies (5/50 and 5/100). Note the abrupt performance drop in SPCC after the condition 25/25. The asterisks and horizontal bars denote statistically significant difference between the pairs of conditions. Only a black asterisk above a condition indicates that in this condition the SPCC/NRMSTE was statistically different from all other conditions. The grey asterisks in NRMSTE denote that the conditions 10/10 and 5/5 differed significantly from all other conditions, but not with respect to each other.

Mentions: The summary results for all subjects and all conditions are given in Figure 6 and 7. For the visual feedback, the average SPCC was 96.9% and the average NRMSTE was 4.4% (Figure 6), with a very stable performance across subjects and trials (i.e., the smallest standard deviation). Comparatively, the performance in this condition was statistically significantly higher than in all other conditions. For the electrotactile feedback, the first statistically significant decrease in SPCC (increase in NRMSTE) was registered between the conditions 100/100 and 25/25 (p < 0.0001, SPCC and NRMSTE). Thus, the frequency of stimulation could be decreased twice to the half of the previous value (i.e., from 100 to 50, and from 50 to 25) without significantly affecting the closed-loop performance with respect to the previous condition. The performance in the conditions 10/10 and 5/5 did not follow the same trend; for the SPCC, the performance in both conditions were significantly lower than the performance in all other conditions, and the same occurred for the NRMSTE except that there was no significant difference in the performance between these two conditions themselves. This change of trend is more pronounced in the SPCC plot (Figure 6a) where there was a marked decrease in the change of the SPCC at a breaking point of 25/25. Delivering the tracking error information at a low rate (as in 5/5) but at a higher stimulation frequency recovered the performance (i.e., 5/5 vs. 5/50 and 5/100). Note the characteristic V (Λ) shape of the SPCC (NRMSTE) plots (Figure 6a and b). In the conditions 5/50 and 5/100, the SPCC and NRMSTE were significantly higher and lower, respectively, than in the conditions 5/5 and 10/10 (p < 0.0001, SPCC and NRMSTE), while there was no significant difference between the performance in the condition 5/50 against the condition 50/50, or between 5/100 and 100/100. Finally, the performance in both conditions 5/50 and 5/100 were not significantly different from the performance in the condition 25/25 in SPCC and NRMSTE. A similar trend was observed for the consistency of performance across conditions. The variability increased with the decrease in the pulse rate (tracking error sampling rate), and then again decreased when the low rate tracking error information was delivered at the high stimulation frequencies. Therefore, the subjects performed better and also more consistently when the feedback was delivered at high frequencies of stimulation (>25 Hz).Figure 6


The impact of the stimulation frequency on closed-loop control with electrotactile feedback.

Paredes LP, Dosen S, Rattay F, Graimann B, Farina D - J Neuroeng Rehabil (2015)

Quality of tracking averaged over all subjects and trials in each condition (VF and FTE/FSTIM). Square Pearson Correlation Coefficient, SPCC (a) and Normalized Root Mean Square Tracking Error, NRMSTE (b). In the VF condition, the performance was significantly higher than in the electrotactile feedback conditions. The closed-loop control performance first steadily worsened (decreasing SPCC, increasing NRMSTE) with the decrease of the stimulation frequency and tracking error sampling rate, but then it almost completely recovered when the low rate tracking error information was delivered using high stimulation frequencies (5/50 and 5/100). Note the abrupt performance drop in SPCC after the condition 25/25. The asterisks and horizontal bars denote statistically significant difference between the pairs of conditions. Only a black asterisk above a condition indicates that in this condition the SPCC/NRMSTE was statistically different from all other conditions. The grey asterisks in NRMSTE denote that the conditions 10/10 and 5/5 differed significantly from all other conditions, but not with respect to each other.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4403675&req=5

Fig6: Quality of tracking averaged over all subjects and trials in each condition (VF and FTE/FSTIM). Square Pearson Correlation Coefficient, SPCC (a) and Normalized Root Mean Square Tracking Error, NRMSTE (b). In the VF condition, the performance was significantly higher than in the electrotactile feedback conditions. The closed-loop control performance first steadily worsened (decreasing SPCC, increasing NRMSTE) with the decrease of the stimulation frequency and tracking error sampling rate, but then it almost completely recovered when the low rate tracking error information was delivered using high stimulation frequencies (5/50 and 5/100). Note the abrupt performance drop in SPCC after the condition 25/25. The asterisks and horizontal bars denote statistically significant difference between the pairs of conditions. Only a black asterisk above a condition indicates that in this condition the SPCC/NRMSTE was statistically different from all other conditions. The grey asterisks in NRMSTE denote that the conditions 10/10 and 5/5 differed significantly from all other conditions, but not with respect to each other.
Mentions: The summary results for all subjects and all conditions are given in Figure 6 and 7. For the visual feedback, the average SPCC was 96.9% and the average NRMSTE was 4.4% (Figure 6), with a very stable performance across subjects and trials (i.e., the smallest standard deviation). Comparatively, the performance in this condition was statistically significantly higher than in all other conditions. For the electrotactile feedback, the first statistically significant decrease in SPCC (increase in NRMSTE) was registered between the conditions 100/100 and 25/25 (p < 0.0001, SPCC and NRMSTE). Thus, the frequency of stimulation could be decreased twice to the half of the previous value (i.e., from 100 to 50, and from 50 to 25) without significantly affecting the closed-loop performance with respect to the previous condition. The performance in the conditions 10/10 and 5/5 did not follow the same trend; for the SPCC, the performance in both conditions were significantly lower than the performance in all other conditions, and the same occurred for the NRMSTE except that there was no significant difference in the performance between these two conditions themselves. This change of trend is more pronounced in the SPCC plot (Figure 6a) where there was a marked decrease in the change of the SPCC at a breaking point of 25/25. Delivering the tracking error information at a low rate (as in 5/5) but at a higher stimulation frequency recovered the performance (i.e., 5/5 vs. 5/50 and 5/100). Note the characteristic V (Λ) shape of the SPCC (NRMSTE) plots (Figure 6a and b). In the conditions 5/50 and 5/100, the SPCC and NRMSTE were significantly higher and lower, respectively, than in the conditions 5/5 and 10/10 (p < 0.0001, SPCC and NRMSTE), while there was no significant difference between the performance in the condition 5/50 against the condition 50/50, or between 5/100 and 100/100. Finally, the performance in both conditions 5/50 and 5/100 were not significantly different from the performance in the condition 25/25 in SPCC and NRMSTE. A similar trend was observed for the consistency of performance across conditions. The variability increased with the decrease in the pulse rate (tracking error sampling rate), and then again decreased when the low rate tracking error information was delivered at the high stimulation frequencies. Therefore, the subjects performed better and also more consistently when the feedback was delivered at high frequencies of stimulation (>25 Hz).Figure 6

Bottom Line: The quality of tracking was assessed using the Squared Pearson Correlation Coefficient (SPCC), the Normalized Root Mean Square Tracking Error (NRMSTE) and the time delay between the reference and generated trajectories (TDIO).The results demonstrated that FSTIM was more important for the control performance than FTE.The outcome of this study can facilitate the selection of optimal system parameters for somatosensory feedback in upper limb prostheses.

View Article: PubMed Central - PubMed

Affiliation: Laboratorio di Cinematica e Robotica, Fondazione Ospedale San Camillo - I.R.C.C.S., Lido di Venezia, Italy. lparede@gwdg.de.

ABSTRACT

Background: Electrocutaneous stimulation can restore the missing sensory information to prosthetic users. In electrotactile feedback, the information about the prosthesis state is transmitted in the form of pulse trains. The stimulation frequency is an important parameter since it influences the data transmission rate over the feedback channel as well as the form of the elicited tactile sensations.

Methods: We evaluated the influence of the stimulation frequency on the subject's ability to utilize the feedback information during electrotactile closed-loop control. Ten healthy subjects performed a real-time compensatory tracking (standard test bench) of sinusoids and pseudorandom signals using either visual feedback (benchmark) or electrocutaneous feedback in seven conditions characterized by different combinations of the stimulation frequency (FSTIM) and tracking error sampling rate (FTE). The tracking error was transmitted using two concentric electrodes placed on the forearm. The quality of tracking was assessed using the Squared Pearson Correlation Coefficient (SPCC), the Normalized Root Mean Square Tracking Error (NRMSTE) and the time delay between the reference and generated trajectories (TDIO).

Results: The results demonstrated that FSTIM was more important for the control performance than FTE. The quality of tracking deteriorated with a decrease in the stimulation frequency, SPCC and NRMSTE (mean) were 87.5% and 9.4% in the condition 100/100 (FTE/FSTIM), respectively, and deteriorated to 61.1% and 15.3% in 5/5, respectively, while the TDIO increased from 359.8 ms in 100/100 to 1009 ms in 5/5. However, the performance recovered when the tracking error sampled at a low rate was delivered using a high stimulation frequency (SPCC = 83.6%, NRMSTE = 10.3%, TDIO = 415.6 ms, in 5/100).

Conclusions: The likely reason for the performance decrease and recovery was that the stimulation frequency critically influenced the tactile perception quality and thereby the effective rate of information transfer through the feedback channel. The outcome of this study can facilitate the selection of optimal system parameters for somatosensory feedback in upper limb prostheses. The results imply that the feedback variables (e.g., grasping force) should be transmitted at relatively high frequencies of stimulation (>25 Hz), but that they can be sampled at much lower rates (e.g., 5 Hz).

No MeSH data available.


Related in: MedlinePlus