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Table 3 Overview of the used input signals and applied processing

From: EMG-driven control in lower limb prostheses: a topic-based systematic review

Ref.

Muscles

Additional sensors and feedback

EMG signal processing (filter order and cut-off frequencies)

Window sampling

Classifier (features)

[64]

Single muscle not contracting during walking

NP

NI

Analog

Thresholding (Raw Sign.)

[29]

GRAC

Load cell on the knee pivot\(^{{\star } {\dag }}\); footswitch\(^{{\star } {\dag }}\);

RECT, BPF (NS)

Analog

NA (ENV)

[24,25,26,27]

Knee FLEX (RFEM/VASI/ VASL), knee EXT (SEMT)

Goniometer\(^{\star }\)

BPF (20–500 Hz)

115–192 ms

LM Network (HIST, ARC)

[56]

HAMS, QUAD

Joint encoder\(^{\dag }\) (visual feedback of knee joint position)

HPF (1st ord, 20 Hz), RECT, LPF (1st ord, 2 Hz), NORM, PCA

2 ms

QDA (ENV)

[14, 23, 62, 63]

VASL, VASM, RFEM, SEMT, BICFL

Joint encoder\(^{\dag }\) (visual and haptic feedback of knee joint position)

BPF (2nd ord, 20–450 Hz), RECT, LPF (2nd ord, 2.5 Hz), NORM; PCA

3 ms

NA (ENV)

[57]

SEMT, SAR, TFL, ADDL, GRAC, RFEM, VASM, VASL, BICFL

Joint encoder\(^{\dag }\) (visual feedback of knee joint position)

NS

200 ms

LDA (MAV, NZC, SSC, WL)

[37]

GASM/SOL, TIBA

Joint encoder\(^{\star }\)

BPF (2nd ord, 10–500 Hz), RECT, LPF (2nd ord, 10 Hz)

50 ms

NARAX (ENV)

[16]

GASM, TIBA

NP

RECT, LPF (3rd ord, 2.5 Hz); PCA

10 ms

NA (MAV)

[67, 68]

GASM/GASL

MoCap system\(^{\star }\); sensorized treadmill\(^{\star }\); control signal visual feedback\(^{{\star } {\dag }}\)

FPF (2nd ord, 100 Hz), RECT, LPF (2nd ord, 4 Hz), NORM

NS

NA (ENV)

[76]

VASM, BICFL, TIBA, GASL

Ankle goniometer\(^{\star }\), accelerometer\(^{\star }\)

RECT, LPF (NS)

NS

Peak detector (ENV)

[11]

VASL, RFEM, SEMT, BICFL

MoCap system \(^{\star }\)

NORM, BPF (4th ord, 30–350 Hz), RECT, LPF (4th ord, 6 Hz), Kalman filter

< 500 ms

NA (ENV)

[39, 40]

TIBA, GASM

Joint position\(^{{\star } {\dag }}\) (visual feedback)

HPF (2nd ord, 20 Hz), RECT, LPF (2nd ord, 2 Hz)

10 ms

NA (ENV)

[98]

GLMAX, GLMED, TFL

Footswitch\(^{{\star } {\dag }}\)

LPF (2nd ord, 1 KHz), HPF (3rd ord, 50 Hz), NORM

NS

Thresholding (ENV)

[70]

VASL, VASM, RFEM, TFL, ADDL, BICFL, SEMM, SEMT

Footswitch\(^{\star }\); load cell\(^{\star }\); MoCap system\(^{\star }\)

NS

NS

Heuristic Tree (IDE, MAV, MDF, MF)

[5]

TIBA, GASM, GASL

Footswitch\(^{{\star } {\dag }}\); potentiometer\(^{{\star } {\dag }}\); encoder\(^{{\star } {\dag }}\); class of movement performed\(^{\star }\) (visual feedback)

HPF (1st ord, 16 Hz), LPF (2nd ord, 300 Hz)

100 ms

STD

[65, 66, 141, 144]

SEMT, SAR, TFL, ADDL, GRAC, VASM, RFEM, VASL, BICFL

Footswitch\(^{\star }\), load cell\(^{{\star } {\dag }}\)

BPF (20–420 Hz)

150 ms

LDA-SVM (MAV, ZCN, WL, SSC, MEC)

[53]

RFEM, BICFL, SEMT, GASM, SOL

2× 6-axis force sensor\(^{\star }\), footswitch\(^{\star }\), joint encoder\(^{\star }\)

RMS, BPS (20–500 Hz)

NS

SVM (NS)

[85]

VASM, SEMT, ADDL, TFL

2× IMU\(^{\star }\)

NS

200 ms

Hidden Markov model (MAV, WL, ZC, SSC)

[15, 110]

VASM, ADDL, TFL, SEMT

MoCap system\(^{\star }\)

NS

NS

SVM (MAV, VAR, MDF, MPF)

[32, 33, 143]

SAR, RFEM, VASL, VASM, BICFL, BICFS, SEMT, TFL, ADDL, GRA

6-axis load cell\(^{{\star } {\dag }}\), 2× IMUs

BPF (20–420 Hz)

150–160 ms

LDA/SVM (MAV, WL, ZCN, SSC, MEC)

[86, 87]

TIBA, GASL, BICF, VASL

Footswitches\(^{{\star } {\dag }}\); IMU\(^{{\star } {\dag }}\)

BPF (4th ord, 20–500 Hz)

100–300 ms

LDA/SVM (MAV, VAR, WL, ZCN, SSC)

[120]

TIBA, PERL, GASL, GASM, VASM, VASL, RFEM, BICFL

Class of movement performed\(^{\star }\) (visual feedback)

BPF (20–450 Hz)

250 ms

LDA (MAV, ZCN, SSC, WL, ARC)

[58, 111]

BICF, RFEM, VASL, VASM, SAR, GRAC, ADDL, TFL + HAMS reinnervation

Load cell\(^{{\star } {\dag }}\), 2× joint encoders\(^{{\star } {\dag }}\), 2× IMU\(^{{\star } {\dag }}\)

BPF (20–450 Hz)

250 ms

same as [140] + Euristic FSM (MEC)

[59, 113, 114, 139, 140]

SEMT, ADDL, TFL, RFEM, BICFL, SAR, GRAC, VASL, VASM

Load cell\(^{{\star } {\dag }}\), 2× joint encoders\(^{{\star } {\dag }}\), 2× IMU\(^{{\star } {\dag }}\)

BPF (20–450 Hz)

250–300 ms

LDA/DBN (MAV, WL, ZCN, SSC, 6ord ARC, MEC)

[17]

GASM, TIBA

Load cell\(^{{\star } {\dag }}\), joint angle encoder\(^{{\star } {\dag }}\), 2× IMU\(^{{\star } {\dag }}\)

PCA

200 ms

LDA (MAV)

[106]

GASL/SOL

NP

NI

NS

Thresholding (Raw Sign.)

[54, 55]

FIBL, BICF

NP

BPF (4th ord, 20–500 Hz)

256 ms

LDA/SVM/NN (38 mixed domain features)

[6]

GASL, SOL, TIBA

Joint angle\(^{{\star } {\dag }}\) (visual feedback)

LPF (7th ord, 5 Hz), NORM

\(\sim\) 1 ms

NA (ENV)

[61]

VASL, BICFL

NP

BPF (20–450 Hz), RECT, LPF (5/10 Hz), NORM

NS

NA (ENV)

[135, 136]

HAMS, QUAD

Load sensors\(^{{\star } {\dag }}\), goniometer\(^{\star }\)

BPF (7th ord, 20–1000 Hz), RECT, LPF (5 Hz)

NS

NA (ENV)

[71, 72, 130]

GASM, TIBA

Joint encoder\(^{{\star } {\dag }}\), torque sensor\(^{{\star } {\dag }}\), 6× load cells\(^{{\star } {\dag }}\)

HPF(4th ord, 80 Hz), RECT, AVR

150–200 ms

NA (ENV)

[19]

VASM, VASL, RFEM, BICF, SEMT

MoCap system\(^{\star }\), sensorized treadmill\(^{\star }\), 2× IMU\(^{{\star } {\dag }}\)

BPF (2nd ord, 30–300 Hz), RECT, LPF (2nd ord, 6 Hz), NORM

300 ms

NA (ENV)

  1. Fields include: paper reference; muscles (input EMG muscle signals employed by the controller); additional sensors and feedback (additional sensor signals employed by the controller and possible feedback provided to the user); EMG signal processing (the sequential processing applied to the input EMG signals; in case of filters, order and cut-off frequencies are included); window sampling (the window length used for the processing and features extraction); classifier (classifier types used on the processed signals and features)
  2. NP not present, NI not implemented, NS not specified, NA not applicable, GRAC gracilis, HAMS hamstring muscles, QUAD quadriceps muscles, VASL vastus lateralis, VASM vastus medialis, RFEM rect femoris, TFL tensor fasciae latae, ADDL adductur longus, BICFL biceps femoris long arm, BICFS biceps femoris short arm, SEMM semimembranosus, SEMT semitendineus, SAR sartorius, GASM gastrocnemius medialis, GASML gastrocnemius lateralis, SOL soleus, TIBA tibialis anterioris, FIBL fibularis longus, GLMAX gluteus maximus, GLMED gluteus medius, FLEX flexors muscles, EXT extensors muscles, BPF band pass filter, HPF high pass filter, LPF low pass filter, RECT rectification, NORM max value normalization, PCA principal component analysis, RMS root mean squared signal, LDA linear discriminant analysis, NARAX non-linear autoregressive neural network with exogenous inputs, QDA quadratic discriminant analysis, ANN artificial neural network, DBN dynamic Bayes network, SVM super vector machine, LM Levenberg-Marquardt, EBA entropy-based adaptation, LIFT learning from testing data adaptation, ENV envelope, IDE integral of differential EMG, MAV mean absolute value, STD standard deviation, MDF median frequency, MF mean frequency, MPF mean power frequency, ZCN zero-crossing number, WL waveform length, SSC sign slope change, ARC autoregressive coefficients, MSAR mean square of ARC, TDAR time-domain and ARC combination, MEC features from mechanical sensors, HIST histogram bin values, VAR variance
  3. \(^{\star }\)Used during calibration phase
  4. \(^{\dag }\)Used during testing phase