kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Real-Time Muscle Fatigue Detection System Based on Multi-Frequency EIM and sEMG for Effective NMES
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0001-7549-0858
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0003-1736-8701
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0003-0565-9907
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0003-3802-7834
2024 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 24, no 14, p. 22553-22564Article in journal (Refereed) Published
Abstract [en]

Neuromuscular electrical stimulation (NMES) is a self-directed home based therapeutic tool in early rehabilitation for musculoskeletal (MSK) conditions. However, the effectiveness of traditional NMES is fundamentally constrained by muscle fatigue. To address this limitation, this work proposes a detection system, which simultaneously records multifrequency electrical impedance myography (EIM) and surface electromyography(sEMG) in real time for time-frequency analysis of muscle activation, contraction, and fatigue. To demonstrate the ability to monitor these muscle physiological states, two experiments involving weightless and weighted dynamic contractions of the biceps brachii muscle were performed. Results from these experiments show synchronous changes in sEMG and EIM spectra during contractions, and clear trends in sEMG’s mean power frequency (MPF) and EIM spectra with fatigue progression. Additionally, the configurable 4-channel NMES has been electrically evaluated for clinical use, demonstrating the feasibility of the proposed system for closed-loop stimulation. This work showcases the potential of sEMG and multi-frequency EIM to enhance the effectiveness of NMES for MSK conditions by capturing the behavior of distinct mechanisms of muscle fatigue.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. Vol. 24, no 14, p. 22553-22564
Keywords [en]
Multi-modal sensing, muscle fatigue, ASIC, bioimpedance (bio-Z) spectroscopy, electrical impedance myography (EIM), surface electromyography (sEMG), closed-loop neuromuscular electrical stimulation (NMES).
National Category
Embedded Systems Medical Laboratory Technologies
Research subject
Electrical Engineering; Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-348831DOI: 10.1109/jsen.2024.3409821ISI: 001273156700098Scopus ID: 2-s2.0-85196109216OAI: oai:DiVA.org:kth-348831DiVA, id: diva2:1878916
Funder
Swedish Foundation for Strategic Research, ITM17-0079
Note

QC 20241011

Available from: 2024-06-27 Created: 2024-06-27 Last updated: 2025-02-09Bibliographically approved
In thesis
1. Fully Integrated Bioimpedance Spectroscopy Interface for Wearable Electrical Impedance Myography
Open this publication in new window or tab >>Fully Integrated Bioimpedance Spectroscopy Interface for Wearable Electrical Impedance Myography
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Multi-Frequency surface Electrical Impedance Myography (MF-sEIM) is a technique that provides valuable electrophysiological information of muscles. This technique measures bio-Z spectroscopy of muscles, and applies Ohm's law by injecting a small-amplitude and high-frequency current into tissues and measuring the voltage response. As biological tissues are electrolytic conductors, this technique provides information on fundamental dielectric properties of tissues, which are an objective biomarker of neuromuscular disorders and have practical value in several muscle healthcare applications. Due to its versatility, simplicity, and ease of integration, this technique is a great candidate to complement stand-alone surface electromyography (sEMG) in wearable devices for continuous monitoring of muscle health. Nonetheless, wearable MF-sEIM imposes challenging requirements on the bio-Z spectroscopy interface. Previously reported solutions fall short of meeting these requirements, or do so with low power efficiency.

This thesis focuses on the research and development of a fully integrated bio-Z spectroscopy interface, which complies with the challenging requirements of wearable MF-sEIM in a power-efficient way. The electrophysiological mechanisms of MF-sEIM and the system-level requirements for clinical relevance were investigated, as MF-sEIM is a relatively novel technique, which requires standarization. From this established set of requirements, the main building blocks of the \mbox{bio-Z} spectroscopy interface, i.e., the current signal generator (CSG), and voltage readout, were developed. The CSG generates pseudo-sine waves through direct digital synthesis (DDS) to obtain the required linearity with high power efficiency. A high-linearity full current-mode CSG was also proposed to comply with the stricter bio-Z accuracy requirements of clinical diagnostics. The voltage readout is based on a low-IF quadrature (I/Q) demodulation architecture and features a pseudo 2-path bandpass (BP) Delta-Sigma ADC to achieve high precision and power-to-noise efficiency. A mixer-first analog front-end (AFE) was also proposed to enable bio-Z spectroscopy measurements employing dry electrodes. The bio-Z interface was integrated with a 16-Channel sEMG AFE and a 4-Channel neuromuscular stimulator (NMES) in an application-specific integrated circuit (ASIC). Experimental results show that the implemented bio-Z spectroscopy interface achieves a comparable performance with the state of the art, while being capable of detecting the large baseline and the time-varying impedances of muscle. A proof-of-concept system, based on the multi-modal ASIC, was developed. This system demonstrates the potential of combining real-time monitoring of MF-sEIM and sEMG for detecting muscle fatigue, enabling efficient closed-loop NMES.

Abstract [sv]

Multifrekvent ytelektroimpedansmyografi (MF-sEIM) är en teknik som ger värdefull elektrofysiologisk information om muskler. Denna teknik mäter bioimpedans-spektroskopi (bio-Z-spektroskpi) av muskler och tillämpar Ohms lag genom att injicera en högfrekvent småsignalström i vävnader och mäta spänningssvaret. Eftersom biologiska vävnader är elektrolytiska ledare, ger denna teknik information om grundläggande dielektriska egenskaper hos vävnader, som är en objektiv biomarkör för neuromuskulära störningar och har praktiskt värde i flera tillämpningar för muskelsjukvård. På grund av dess mångsidighet och enkel integration är denna teknik en utmärkt kandidat för att komplettera fristående ytelektromyografi (sEMG) i bärbara enheter för kontinuerlig övervakning av muskelhälsa. Icke desto mindre ställer bärbar MF-sEIM utmanande krav på bio-Z-spektroskopigränssnittet. Tidigare rapporterade lösningar uppfyller inte dessa krav, eller gör det med låg energieffektivitet.

Denna avhandling fokuserar på forskning och utveckling av ett helt integrerat bio-Z-spektroskopigränssnitt, som uppfyller de utmanande kraven för bärbar MF-sEIM på ett energieffektivt sätt. De elektrofysiologiska mekanismerna för MF-sEIM och kraven på systemnivå för klinisk relevans undersöktes, eftersom MF-sEIM är en relativt ny teknik som kräver standardisering. Från de definerade kraven på systemnivå utvecklades huvudbyggstenarna för bio-Z-spektroskopigränssnittet, dvs. strömsignalgeneratorn (CSG) och spänningsavläsningen. CSG genererar pseudo-sinusvågor genom direkt digital syntes (DDS) för att erhålla den erforderliga linjäriteten med hög energieffektivitet. En CSG i fullströmsläge med hög linjäritet föreslogs också för att uppfylla de striktare noggrannhetskraven på bioimpedansmätning för klinisk diagnostik. Spänningsavläsningen är baserad på en demoduleringsarkitektur med låg IF-kvadratur (I/Q) och har en pseudo 2-vägs bandpass (BP) Delta-Sigma ADC för att uppnå hög precision och energi till brus effektivitet. En mixer-framför analog front-end (AFE) föreslogs också för att möjliggöra bio-Z-spektroskopimätningar med användning av torra elektroder. Bio-Z-gränssnittet integrerades med en 16-kanals sEMG AFE och en 4-kanals neuromuskulär stimulator (NMES) i en applikationsspecifik integrerad krets (ASIC). Experimentella resultat visar att det implementerade bio-Z-spektroskopigränssnittet uppnår en prestanda som är jämförbar med den senaste tekniken, samtidigt som den kan detektera storsignalsimpedansen hos muskler och dess tidsvariation. Ett prototyp, baserat på den multimodala ASIC, utvecklades. Detta system visar potentialen i att kombinera realtidsövervakning av MF-sEIM och sEMG för att upptäcka muskeltrötthet, vilket möjliggör effektiva NMES med återkoppling.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2024. p. xix, 84
Series
TRITA-EECS-AVL ; 2024:62
Keywords
Musculoskeletal health, bioimpedance (bio-Z) spectroscopy, electrical impedance myography (EIM), biomedical modeling, ASIC, ultra-low power, high-precision, sinusoidal signal generator, readout, analog front-end, bandpass delta-sigma ADC, multi-modal sensing., Muskuloskeletal hälsa, bioimpedans-spectroscopi (bio-Z-spektroskpi), elektroimpedansmyografi (EIM), biomedicinsk modellering, ASIC, ultralåg energi, hög precision, sinusformad signalgenerator, avläsning, analog front-end, bandpass delta-sigma ADC, multimodal avkänning.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-352340 (URN)978-91-8106-022-5 (ISBN)
Public defence
2024-09-27, https://kth-se.zoom.us/j/2593490856, Ka-Sal C, Electrum, Kistagången 16, Kista, 13:00 (English)
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research, ITM17-0079
Note

QC 20240829

Available from: 2024-08-29 Created: 2024-08-28 Last updated: 2024-08-29Bibliographically approved
2. Electrical Stimulator and Surface Electromyography Integrated Circuits for Musculoskeletal Healthcare
Open this publication in new window or tab >>Electrical Stimulator and Surface Electromyography Integrated Circuits for Musculoskeletal Healthcare
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis presents an innovative approach to the development of a fully integrated multi-channel neuromuscular electrical stimulator (NMES) system and a multi-channel surface electromyography (sEMG) acquisition system for musculoskeletal (MSK) healthcare applications. The main objective is to integrate therapeutic and diagnostic tools into a compact wearable device, enabling closed-loop electrical therapy. By leveraging advancements in semiconductor technology, this thesis explores the implementation of application-specific integrated circuits (ASIC) to combine high-voltage (HV) NMES and low-voltage sEMG signal acquisition circuits on a single chip using a 180 nm bipolar-CMOS-DMOS technology.  

The research addresses several key challenges in existing NMES and sEMG systems: the need for a compact, multi-channel NMES device; the need for safe electrical muscular stimulation; the need for spatiotemporal information through multi-channel acquisition; and the need for high channel counts and efficient chip area utilization. To overcome these challenges and advance the NMES technology, this thesis proposes several innovative circuit solutions, including a configurable HV-tolerant multi-channel stimulator, an integrated fail-safe protection circuit, and an inductorless on-chip HV generator. Additionally, channel-sharing techniques for multi-channel biopotential acquisition are comprehensively explored, and a novel frequency-division multiplexed architecture is proposed, featuring low noise, low power consumption, and minimized system complexity. 

A significant contribution of this thesis work is the integration of multi-channel NMES and sEMG systems in an ASIC, leading to the development of a real-time embedded system for wearable medical applications. This embedded system incorporates the proposed ASIC for bidirectional interfacing with muscles and an off-the-shelf microcontroller for data acquisition, signal processing, and stimulation pattern control. The proposed system facilitates the continuous collection of vital physiological conditions (e.g., motion intention, contraction force, and fatigue level) of the human muscular system, enabling timely adjustments and interventions via electrical stimulation. In-vivo experimental results showcase its potential to enhance electrical therapy outcomes through closed-loop control and pave the way for improved patient care.

Abstract [sv]

Denna avhandling presenterar ett innovativt tillvägagångssätt för utveckling av ett fullt integrerat flerkanals neuromuskulärt elektriskt stimulator (NMES) system och ett flerkanals ytelektromyografi (sEMG) insamlingssystem för applikationer inom muskuloskeletal hälsovård. Huvudmålet är att integrera terapeutiska och diagnostiska verktyg i en kompakt bärbar enhet, vilket möjliggör sluten elektrisk terapi. Genom att utnyttja framsteg inom halvledarteknologi undersöker denna avhandling implementeringen av applikationsspecifika integrerade kretsar (ASIC) för att kombinera högspännings (HV) NMES och lågspännings sEMG-signalupptagningskretsar på ett enda chip med hjälp av en 180 nm bipolär-CMOS-DMOS-teknologi.

Forskningen adresserar flera centrala utmaningar i befintliga NMES- och sEMG-system: behovet av en kompakt flerkanals NMES-enhet; behovet av säker elektrisk muskelstimulering; behovet av spatiotemporal information genom flerkanals signalupptagning; samt behovet av hög kanalantal och effektiv chipytanvändning. För att övervinna dessa utmaningar och främja NMES-teknologin, föreslår denna avhandling flera innovativa kretsslösningar, inklusive en konfigurerbar HV-tolerant flerkanals stimulator, en integrerad failsafe skyddskrets och en induktorlös on-chip HV-generator. Dessutom utforskas kanaldelningstekniker omfattande, och ett nytt frekvensdelningsmultiplexat flerkanals biopotential-insamlingssystem utvecklas, som kännetecknas av låg brusnivå, låg strömförbrukning och minimerad systemkomplexitet.

En betydande insats i denna avhandling är integrationen av flerkanals NMES- och sEMG-system i en ASIC, vilket leder till utvecklingen av ett realtids inbäddat system för bärbara medicinska applikationer. Detta inbäddade system inkorporerar den föreslagna ASIC för tvåvägsgränssnitt med muskler och en standard mikrokontroller för datainsamling, signalbehandling och styrning av stimulansmönster. Det föreslagna systemet underlättar kontinuerlig insamling av vitala fysiologiska förhållanden (t.ex. rörelseavsikt, kontraktionskraft och trötthetsnivå) i människans muskelsystem, vilket möjliggör snabba justeringar och interventioner via elektrisk stimulering. In-vivo experimentella resultat visar dess potential att förbättra resultaten av elektrisk terapi genom sluten styrning och banar väg för förbättrad patientvård.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2024. p. xvii, 94
Series
TRITA-EECS-AVL ; 2024:65
Keywords
neuromuscular electrical stimulation, surface electromyography, musculoskeletal healthcare, application-specific integrated circuits, bipolar-CMOS-DMOS technology, high-voltage generator, biopotential acquisition, frequency-division multiplexing, closed-loop electrical therapy, wearable medical device, embedded system, neuromuskulär elektrisk stimulering, ytelektromyografi, muskuloskeletal hälsovård, applikationsspecifika integrerade kretsar, bipolär-CMOS-DMOS-teknologi, högspänningsgenerator, biopotentialinsamlingssystem, frekvensdelningsmultiplexering, sluten loop elektrisk terapi, bärbar medicinsk enhet, inbäddat system
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-353846 (URN)978-91-8106-035-5 (ISBN)
Public defence
2024-10-18, Ka-Sal C, Electrum, Kistagången 16, Kista, 10:00 (English)
Opponent
Supervisors
Note

QC 20240925

Available from: 2024-09-25 Created: 2024-09-24 Last updated: 2025-02-06Bibliographically approved

Open Access in DiVA

fulltext(16735 kB)148 downloads
File information
File name FULLTEXT01.pdfFile size 16735 kBChecksum SHA-512
3ebf813528e0254036f74df4f20fd0338b4d0049b0222546094e296d1f9358560954c8a5627312d981e2aead229e7f938a56fc4dc031399e465a1c7817a679ef
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Fernández Schrunder, AlejandroHuang, Yu-KaiRodriguez, SaulRusu, Ana

Search in DiVA

By author/editor
Fernández Schrunder, AlejandroHuang, Yu-KaiRodriguez, SaulRusu, Ana
By organisation
Electronics and Embedded systems
In the same journal
IEEE Sensors Journal
Embedded SystemsMedical Laboratory Technologies

Search outside of DiVA

GoogleGoogle Scholar
Total: 148 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 524 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf