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Scientific Paper / Artículo Científico |
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https://doi.org/10.17163/ings.n33.2025.04 |
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pISSN: 1390-650X / eISSN: 1390-860X |
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PROTOTYPE OF A REMOTELY CONTROLLED MULTICHANNEL SURFACE MUSCLE STIMULATOR |
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PROTOTIPO DE ESTIMULADOR MUSCULAR SUPERFICIAL MULTICANAL CONTROLADO REMOTAMENTE |
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P.
Silverio-Cevallos1,* C. J.
Tierra-Criollo1,* |
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Received: 13-11-2023, Received after review: 29-05-2024, Accepted:
05-11-2024, Published: 01-01-2025 |
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Abstract |
Resumen |
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Multichannel
Functional Electrical Stimulation (FES) technology is widely employed in artificial
motor control research. This study presents the design and evaluation of a
four-channel, remotely controlled surface electrical muscle stimulator
prototype. The prototype introduces a modern alternative for the control
block, employing a Wi-Fi-enabled solution based on the ESP32 microcontroller.
This controller enables remote configuration of activation sequences for
individual channels and supports extensive customization of parameters for a
biphasic waveform stimulus. The current signal is demultiplexed into four
outputs. Additionally, this study provides a detailed functional evaluation
of the amplification stage and examines the load-dependent limitations of the
output current magnitude. Preliminary experimental testing demonstrates the
prototype’s ability to generate controlled stimulation sequences in hand
muscles. The prototype’s functional and experimental performance suggests its
potential application in artificial motor control research. |
La tecnología de estimulación eléctrica funcional (EEF) multicanal se utiliza actualmente en la investigación del control motor artificial. Este trabajo describe el diseño y evaluación de un prototipo de estimulador eléctrico muscular de cuatro canales controlado remotamente. El prototipo propone una alternativa moderna para el bloque de control, utilizando el microcontrolador wifi/ESP32. Este permite una secuencia de activación de canales configurable de manera remota y una extensiva configuración de los parámetros de un estímulo en forma de onda bifásica. La señal de corriente se demultiplexa en cuatro salidas. Este estudio también contribuye detallando la evaluación funcional de la etapa de amplificación y estableciendo la dependencia de la magnitud de la carga en los límites de la corriente de salida. La prueba experimental preliminar demuestra la capacidad del prototipo para generar secuencias de estimulación controladas en los músculos de la mano. El desempeño funcional y experimental del prototipo sugiere su potencial uso para investigaciones del control motor artificial. |
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Keywords: Multichannel Functional Electrical
Stimulator, Muscle Stimulator, Artificial Motor Control |
Palabras clave: estimulador eléctrico funcional multicanal, estimulador muscular, control motor artificial |
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1,*Biomedical
Engineering Research Group - GIIB, Universidad Politécnica Salesiana, Ecuador. Corresponding
author ✉: psilverio@est.ups.edu.ec. 2
Biomedical
Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and
Research in Engineering (Coppe), Federal University of Rio de Janeiro, Brazil.
Suggested citation: Silverio-Cevallos, P., Maita Cajamarca, J., Molina-Vidal, D. A., Tierra-Criollo, C. J. and Cevallos- Larrea, P. “Prototype of a remotely controlled multichannel surface muscle stimulator,” Ingenius, Revista de Ciencia y Tecnología, N.◦ 33, pp. 38-48, 2025, doi: https://doi.org/10.17163/ings.n33.2025.04. |
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1. Introduction Neurodegenerative disorders, such as
Parkinson’s disease (PD), spinal muscular atrophy, and amyotrophic lateral
sclerosis, among others [1–3], have a profound impact on the nervous system,
frequently affecting motor functions. Common symptoms associated with these
motor disorders include difficulty initiating and coordinating smooth
muscular movements, inhibition of involuntary movements, challenges with
postural adjustment, progressive limb muscle weakness, and muscle atrophy
[4–6]. Electrical
stimulation therapy plays a pivotal role as a non-pharmacological treatment
for motor disorders associated with neurodegenerative diseases. Common
non-invasive techniques include Transcutaneous Electrical Nerve Stimulation
(TENS) and Functional Electrical Stimulation (FES). TENS primarily targets
afferent nerve fibers to mitigate muscle atrophy, alleviate pain, enhance
muscle strength, and support functional movement therapy [7]. In contrast,
FES stimulates motor nerves to induce contractions in weak or paralyzed
muscles. This technique is particularly effective for patients with motor
impairments, such as those experiencing paralysis or severe muscle weakness
[8]. Artificial motor
control through FES is an assistive strategy designed to achieve functional
and intentional movements by inducing controlled contractions in targeted
muscle groups [9]. The therapeutic potential of this technique has been
extensively studied in various conditions, including Parkinson’s disease
[10], paraplegia [11] and neuroprosthetics [12]. Research conducted
by Qi Wu et al. [13] and Masdar et al. [14] demonstrated the efficacy of
electrical stimulation in restoring and maintaining muscle activity in
paralyzed patients with spinal cord injuries and related neural deficits.
Furthermore, studies by Hai-Peng Wang et al. [15] and Keller T. [16]
highlighted the use of electrical stimulation to enhance motor control and
support motor function training in stroke patients. Despite the
availability of various commercial electrical stimulation technologies,
experimental paradigms in artificial motor control often require stimulators
with capabilities that surpass those offered by standard TENS and FES
technologies [17, 18]. For instance, advanced features such as multichannel
stimulation with remotely programmable output patterns and customizable
stimulus parameters are critical in this context [19]. However, detailed
accounts of such advanced electrical stimulation prototypes remain limited.
One notable example is the multichannel programmable stimulator prototype
developed by Qi Xu et al. [20]. |
Similarly, Hai-Peng
Wang et al. [15] proposed a FES stimulator capable of multiplexing signals
from an
First, many prior
studies rely on electronic control blocks that are difficult to procure or
replicate due to inaccessible developer tools and documentation [15], [19].
For instance, the prototypes described in [15], [20] employ outdated
controller technologies. Second, these
reports often lack comprehensive descriptions of performance evaluations and
the limitations of signal amplification and current source circuitry,
impeding reproducibility and validation efforts. To address the need
for contrasting and replicable research in advanced motor control, it is
essential to explore modern and easily replicable technologies for electrical
stimulation. This study aims to design and evaluate a prototype multichannel,
wireless surface electrical stimulator for FES. The design specifications
include remote control functionality via a smartphone and the use of widely
available electronic components with extensive development resources to
facilitate replication. Additionally, the
prototype is capable of generating programmable sequences of multiplexed
rectangular biphasic signals across four isolated channels. The controller
block is implemented using the ESP32 wireless microcontroller, a widely
adopted platform known for its large support community, versatility, and
scalability [21–24]. Furthermore, a
preliminary experimental test was conducted to assess the prototype’s ability
to generate sequential, programmable muscle contractions in hand muscles,
captured using a sensorized glove equipped with
accelerometers. 2. Materials and methods 2.1. Design Methodology Figure 1 illustrates the general architecture
of the Multichannel Surface Electrical Stimulator (MSES). The system consists
of two primary components: (i) a hardware module
that generates biphasic waveform current stimuli across four asynchronously
activated channels, and (ii) a software module, implemented as a smartphone
application, which allows users to configure stimulation parameters,
including magnitude, total period, inter-stimulus interval, and stimulation
sequences across output channels. Communication between the hardware and software
modules is facilitated through a wireless (Wi-Fi) connection. |
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2.2. Hardware The hardware architecture consists
of three main blocks: sourcing, control, and current stimulus generation, as
depicted in Figure 2.
Figure 1. General architecture of the MSES
Figure 2. Hardware architecture of MSES The Sourcing Block
is powered by a 5 VDC battery, generating two isolated voltage levels. A low
voltage level of +/- 5 VDC is provided by an isolated DC-DC converter (model
THM 10-0521WI) to power the digital |
circuits within the control block
and the analog signal conditioning circuit in the initial stage of the
current stimulus generator. Additionally, ahigh voltage level of +/- 60 VDC
is generated using an isolated DC-DC converter (model R05-100B) to supply the
current stimulus generator. The Control Block is
managed by an ESP32 microcontroller (Ten silica Xtensa, 32-bit, LX6
processor), featuring integrated wireless communication capabilities. The
firmware algorithm processes incoming commands — such as start, stop, update
stimulus, and channel sequence — as well as stimulus parameters, including
anodic and cathodic current periods, magnitude, and inter-channel intervals,
from the remote application. The control block sets the low-level stimulus
amplitude using an 8-bit digital-to-analog converter (DAC) connected to a
unity-gain amplifier circuit, providing a DAC output range of 0 to 3.3 VDC.
Additionally, it performs two critical functions within the current stimulus
generator block: reversing the amplified magnitude of the electrical pulse to
produce a biphasic stimulus and demultiplexing the stimulus to a designated
output channel. The Electrical
Current Stimulus Generator comprises four main stages. The first stage
converts the low-level voltage from the DAC signal into a highvoltage-
driven current signal (+/-60 VDC), adhering to the recommendations outlined
in [15]. Specifically, the DAC signal is fed into a voltage-to-current
converter circuit, commonly referred to as a transconductance amplifier. The
resulting current signal drives two current amplification circuits (Wilson
Current Mirror - WCM), each powered by the levels HV+ and HV-, creating a
constant current flow through OUT+ and OUT- when a load is connected, as
depicted in Figure 3. In the WCM circuit, using resistor values (R+ and R-)
lower than 1 kΩ results in signal degradation
at the output, particularly for of ≈ 1kΩ. This study adopted
resistor values of 2.4 kΩ for R+ and R-, which
demonstrated the lowest noise levels at the output and minimized voltage drop
across VCE in transistors Q1 and Q2. The specific values
of R+ and R- also influence the maximum voltage at OUT+ and OUT-,
consequently limiting the maximum current output [15]. |
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Figure 3. Electrical
Schematic of the Voltage-to-Current Converter (V-to-C) Circuit and the Wilson
Current Mirror (WCM) Circuits. The V-to-C circuit uses Op Amps TLC2252 (OA1
and OA2) and a variable resistor (RAdj) to adjust the working current range.
The WCM employs NPN transistors (2N6517, Q2) with resistor R- to amplify the
signal to HV-, and PNP transistors (2N6520, Q1) with resistor R+ to achieve
HV+ |
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In the second stage,
the output terminal of the WCM is connected to a phase inverter circuit
featuring a programmable four-switch H-bridge topology controlled by the
control block. This circuit reverses the direction of current flow through
the load to generate a biphasic waveform or disables stimulus transmission
entirely. The hardware can be configured to produce a square waveform with
specified durations for the anodic cycle (anodic current, S1 switches ON),
cathodic cycle (cathodic current, S2 switches ON), and the interval between
these cycles. Finally, the biphasic signal passes through a selector circuit
(demultiplexer) that, under the control of the block, directs the stimulus to
one of the four available outputs. 2.3. Software This project utilized the Modular
platform to develop a smartphone-based user interface application, as
depicted in Figure 4 [25]. The application enables users to adjust stimulus
parameters (Figure 4a), including stimulus magnitude (I+, I-), total period
(T), anodic current period (Tp, positive), cathodic
current period (Tn, negative), and two unstimulated periods: Tc1 (between Tp and Tn) and Tc2 (following Tn). When stimulation is
applied to a specific channel, the stimulus is delivered repeatedly to that
output over a user-configurable period, Tr, ensuring consistent mechanical
contractions that may not be achievable with a single square stimulus pulse.
The user interface supports real-time updates of stimulation parameters in
the hardware and manages the application of stimuli (Figure 4b). During multichannel
stimulation, the configured stimulus is sequentially directed to the enabled
channels in ascending order(i.e., from channel 1 to channel 4). |
Figure 4. User Interface Application. (a)
Waveform panel displaying stimulus parameters. (b) Controls for inputting
stimulus parameters and managing the stimulation protocol 2.4. Performance Tests The evaluation of the system’s
performance involves determining the operational limits of the stimulus
parameters and the multichannel stimulation paradigm. The first test assessed
the stimulus magnitude by activating a single output (channel 1) and varying
both the stimulus magnitude and the resistive load values (1 kΩ, 5 kΩ, and 10 kΩ). During this test, the DAC output was set to
nine fixed values within its dynamic range, enabling the derivation of an
equation relating the digital values configured in the DAC to the output
current levels. The second test measured the stability of the electrical |
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current and the rising and falling
times of the square wave stimulus under varying load conditions. The test
used a fixed current level of 5 mA, with period values for Tp, Tn, Tc1, Tc2, and total period (T) set to 25 ms, 25 ms, 10 ms, 40 ms, and 100 ms, respectively (F = 10 Hz). Resistive load values of 1,
3.3, 5.6, 10, 12, and 20 kΩ were applied. The
final test evaluated the system’s capability to sequentially redirect the
configured stimulus across multiple channels, following the multichannel
stimulation paradigm. This test simultaneously measured two channels
(channels 1 and 2), using stimulus magnitudes of 2.5 mA and 5 mA, periods Tp and Tn of 25 ms and 40 ms, respectively, and a Tr period equal to the total
period T (one stimulus per channel). 2.5. Preliminary application test This preliminary application test
served as an initial evaluation of the proposed technology, without extensive
testing on healthy individuals or patients with neurodegenerative diseases.
The primary objective was to assess the system’s ability to generate
controlled electrical current stimuli across multiple channels, inducing
intentional finger contractions in a predetermined sequence. The experiment
was conducted in the Laboratory of the Biomedical Engineering Research Group
(GIIB-UPS) with two participants, both authors of this study. Both
participants reported being in good health, with no history of muscular or
neurological disorders, cardiac conditions, or pacemaker use. This test
adhered to the ethical principles outlined in the Declaration of Helsinki
[26], and informed consent was obtained from both participants. Three
stimulation regions (R1, R2, R3) on the forearm and a ground region (RG) on
the olecranon were identified for electrode placement (Figure 5a). This
configuration followed a previously established protocol [27] to elicit
contractions in the index, middle, and ring + little fingers, corresponding
to stimulation in R1, R2, and R3, respectively. Before initiating
multichannel stimulation, the stimulus magnitude was determined to elicit
visible but painless muscular contractions. To achieve this, singlechannel stimulation was applied, gradually
increasing the current level from 0 mA until a visible contraction was
observed, ensuring the absence of pain for the participant. The parameters
selected for the multichannel test were as follows: total period (T) of 20 ms, anodic (Tp) and cathodic
(Tn) phases of 200 μs, an interphase interval
(Tc1) of 100 μs, a repetition interval (Tr) of
5 s, and a stimulus magnitude of approximately 5 mA. These stimulation levels
align with those used in previous studies [28]. |
Figure 5. (a) Electrode placement regions
for forearm stimulation(R1, R2, R3) and reference in RG., (b) Sensing glove
with MPU6050 sensors attached to index, middle, ring, and little fingers For multichannel
stimulation, three channels (C1, C2, C3) and two stimulation modes were
utilized. In the first mode, channels C1, C2, and C3 were connected to
regions R1, R2, and R3, respectively. In the second mode, the connections
were reconfigured to R2, R3, and R1, respectively. In both modes, the
stimulator was programmed with a sequential stimulation pattern of C1 →
C2 → C3. A sensing glove was
developed to objectively measure finger movement in response to each
stimulus. This glove incorporates four acceleration sensors (MPU6050), each
attached to the index, middle, ring, and little fingers (Figure 5b). The
sensors communicate with an AT mega 328 microcontroller (Arduino Nano) via
the I2C protocol, and the recorded data are stored in a digital .txt file
using serial communication. The sensor data facilitate the calculation of the
rotation angle (pitch) for each finger as it flexes. Before stimulation, the
participant was instructed to maintain their hand in a natural, relaxed
position (rest), during which the initial mean rotation angles were recorded.
Consequently, the sensor data are expressed as values relative to the sensors
initial positions. |
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3. Results and discussion 3.1. Performance Indicators The DAC’s output varied linearly
within a range of -0.08 to 2.93 V for input values between 0 and 255 digital
units. To achieve a 10 mA output in the electric current generator block from
the maximum DAC output voltage, RAdj in the V-to-C circuit (Figure 3) was set
according to the equation: RAdj = V DACmax/Imax,
that is 2.93V/10mA = 293Ω. RAdj adjusts the current level at the output
of the V-to-C circuit, which is subsequently amplified through the WCM
circuit (Figure 3). Figure 6a illustrates a directly proportional relation
between the voltage across the load and the DAC levels. The output voltage
increases with the load value to maintain a fixed current level at the
output. However, as the load magnitude increases, both the output voltage and
the |
current level reach saturation.
This behavior is attributed to the maximum voltage available at the OUT+/–
terminals during the performance test, which reached a maximum value of 77.6
VDC. It is important to note that during experimental tests, the DC-DC
converters were set to provide+/-64 V for +/- HV. Figure 6b demonstrates an
approximately linear relationship between the output current and the DAC
control variable for three resistive loads (1, 5, and 10 kΩ).
A maximum current of 7.63 mA was achieved for the 10 kΩ
load, consistent with the saturation explanation provided earlier. For the 5 kΩ load, the linear trend was calculated using
least-squares regression to determine the output/input relationship. This
analysis yielded the equation: Iout(mA) = (0.038×
digital value) −0.0819, is integrated into the firmware algorithm to
convert the stimulus magnitude, expressed in units of electric current, into
digital DAC values: digital value = (1000 × Iout +
81.9)/38.8. |
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Figure 6. Voltage and current
measurements for a single stimulus applied to resistive loads of 1, 5, 10 kΩ, within the range of the DAC control variable.
(a) Load output voltage vs DAC Levels, (b) Load output current vs DAC Levels |
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Figure 7a
illustrates the waveform of the output current signal for load resistances
ranging from 1 kΩ to kΩ.
Overall, the measured magnitude of the biphasic stimulus remains stable, with
a mean value of 4.38 mA and a standard deviation of +/- 618 μ A (12.37 %
relative to the stimulus magnitude). The maximum variation (14.5 %) was
observed at a load of 20 kΩ. Figure 7b depicts
the signal transition time measurements for changes between stimulus
magnitudes of 10 % to 90 % |
and vice versa. The average rise
time was 10.1 μs, with minimum and maximum
times of 1.6 μ s and 11.7 μ s, respectively. Some non-linearities
in signal magnitude, such as a peak at the start of the transition, were
noted as the load resistance decreased. Conversely, the average fall time was
10.9 μ s, with minimum and maximum times of 0.4 μ s and 11.3 μ
s, respectively. In general, both rise and fall times increased slightly as
the load resistance increased. |
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Figure 7. Stimulus
waveform parameters for different load resistances: (a) Stability of the
biphasic stimulus waveform current, (b) Rise and fall times for a stimulus
magnitude of 5 mA |
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Names should be abbreviated
using initials only. The amplitudes and periods generated by the MSES closely
matched those configured in the user interface, as shown in Figure 8. This
figure illustrates a sequence of stimuli generated on channels one and two,
with variations in some stimulus parameters. In Figure 8a, the values for |
Tp, Tn, and magnitude were 40 ms, 40 ms, and 2.72 mA,
respectively, while in Figure 8b, these values were 25 ms,
25 ms, and 5.26 mA. The total period (T), which was
set equal to Tr for this test, was 100 ms.
Additionally, Figure 8 demonstrates the absence of interchannel
interference during sequential stimulation on channels one and two. |
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Figure 8. Output of two synchronously applied channels. (a)
signal with Tp and Tn of 40 ms
and (b) signal Tp and Tn of 25 ms. |
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3.2. Application test Finger contraction and relaxation
events, along with their relationship to the two proposed stimulation sequences,
were analyzed using the signals recorded by the |
sensorized glove for participants #1 and #2
(Figure 9). Overall, the sensor data demonstrated that specific finger
movement patterns are primarily influenced by the stimulated region, with
less influence from the stimulation sequence (R1 → R2 → R3 or R2 →
R3 → R1). |
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Figure 9. Rotation angles
obtained from acceleration sensors attached to the sensitized glove. The
movement patterns correspond to sequences R1 → R2 → R3 for (a)
and (c), and R2 → R3 → R1 for (b) and (d), and participant #1
with (a) and (b) and #2 with (c) and (d) |
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For example,
in participant #1, stimulation of R2 predominantly caused contraction of the
middle finger and relaxation tendencies in the ring and pinky fingers. This
pattern was observed in both repetitions of the sequence R1 → R2 →
R3 (Figure 9a) and once in the sequence R2 → R3 → R1 (Figure 9b).
Stimulation sequences beginning at R2 (from the resting state) did not
generate signals associated with ring and pinky finger relaxation.
Additionally, stimulation of R3 induced contraction of the ring, middle, and
pinky fingers for both sequences in participant #1. Conversely, stimulation
of R1 generally exhibited a relaxation effect, particularly when any fingers
were previously contracted. This effect was evident in the sequence R2 →
R3 → R1 (Figure 9b) and during the second R1 stimulation in the
sequence R1 → R2 → R3 (Figure 9b). When stimulation began at R1
(after the resting state, Figure 9a), a contraction movement was observed in
the ring finger. The contraction patterns observed in participant #2 were
similar to those noted in participant #1. In summary, the
stimulation sequence R1 → R2 → R3 (Figure 9c) elicited the
following pattern of movements: no finger contraction (R1) →
predominant |
contraction of the middle finger
(R2) → predominant contraction of the ring finger, with less pronounced
contractions of the middle and pinky fingers (R3). Conversely, the sequence
R2 → R3 → R1 (Figure 9d) produced the following movement pattern:
predominant contraction of the middle finger (R2) → predominant
contraction of the ring finger, along with less pronounced contractions of
the middle and pinky fingers (R3) → no contraction or relaxation of
previously contracted fingers (R1). Predominant contraction events for both
participants and stimulation sequences are summarized in Table 1. Table 1. Summary of finger
contractions or relaxing events for two stimulation sequences in both
participants (P#1, P#2).
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4. Conclusions This study presents a prototype
for a Functional Electrical Stimulation (FES) multichannel system capable of
delivering programmable sequences of multiplexed rectangular biphasic signals
across four isolated channels, with operational control via a smartphone. The proposed
prototype offers several technological and documentation advancements
compared to prior research on similar electrical stimulation technologies.
First, the current design employs the widely accessible, cost-effective, and
well-supported ESP32 wireless microcontroller. This modern controller
simplifies the stimulator’s electronic control block, addressing limitations
in earlier designs that relied on outdated controllers, as noted in [15],
[20]. This modification provides a replicable alternative for the control
block of stimulation technologies, potentially facilitating further research
in artificial motor control. Second, this study provides detailed performance
data for the circuitry within the stimulus generation block, a feature not
addressed in prior designs of multichannel electrical stimulators [15],
[20].Specifically, the current output exhibited a strong dependence on the
adjustment of resistors RAdj and Rvg (Figure 3).
While the circuit effectively generates constant current stimuli, the maximum
current level and the dynamic range of the amplifier stage are constrained by
increases in the load magnitude connected to the output. Third, this
prototype introduces a scalable multiplexing scheme utilizing a combination
of optocoupler and trial per channel. This topology enables straightforward
replication to expand the number of channels as needed. Additionally, the preliminary
tests demonstrated the system’s capability to generate programmable sequences
of controlled muscle contractions. The results suggest
that the prototype is well-suited for integration into extended experimental
protocols for multichannel sequential muscle stimulation. Future work will
focus on developing a miniaturized, embedded version of the prototype in the
form of a handheld device equipped with an accelerometer. This enhanced
iteration will facilitate broader experimental applications of multichannel
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