WO2022005271A1

WO2022005271A1 - System and method for real-time monitoring progression of low back pain rehabilitation

Info

Publication number: WO2022005271A1
Application number: PCT/MY2020/050111
Authority: WO
Inventors: Fatimah IBRAHIM; Aung THIHA; Karunan JOSEPH; Nor Amirah MOHD NOH; Jongman CHO
Original assignee: University Of Malaya
Priority date: 2020-06-30
Filing date: 2020-10-19
Publication date: 2022-01-06
Also published as: AU2020456975A1; JP2023533517A

Abstract

The present invention discloses a system and a method for monitoring a progression of low back pain rehabilitation in a real-time manner. The system comprises a wearable electromyography, EMG, assembly comprising a plurality of detection electrodes deployed on erector spinae muscles at a lumbar region of vertebrae L4 and L5, a signal detection module, an acquisition and transmission module, an inertia measurement module, and a monitoring and reporting unit. The monitoring and reporting unit determines, based on digital EMG signal, a flexion relaxation ratio, FRR, and an extension relaxation ratio, ERR, associated with the said erector spinae muscles, and compares the same against that of a historical data to determine the said rate of improvement or deterioration.

Description

SYSTEM AND METHOD FOR REAL-TIME MONITORING PROGRESSION OF LOW BACK PAIN REHABILITATION

FIELD OF THE INVENTION

The present invention generally relates to low back pain rehabilitation. More particularly, the present invention relates to an improved system for monitoring a progression of low back pain rehabilitation in a real-time manner, and a method thereof.

BACKGROUND OF THE INVENTION

Low back pain refers to pain of variable duration in an area of the anatomy afflicted so often that it is has become a paradigm of responses to external and internal stimuli. Such pain is known as a cause of disability and inability to work, as an interference with the quality of life, and as a reason for medical consultation. Most low back pain is the results of an injury, such as muscle sprains or strains due to sudden movements or poor body mechanics while lifting heavy objects, or the results of certain diseases such as cancer of the spinal cord, a ruptured or herniated disc, sciatica, arthritis, kidney infections, and infections of the spine. There are several medical treatments for low back pain, which include medications, medical appliances, and physical therapy as well as surgery. The goals of these treatments are to decrease back pain, increase function, and teach the patient a maintenance program to prevent future back problems. The progression of low back pain rehabilitation of a patient must be observed and evaluated correctly and continuously so that proper treatments can be prescribed. The existing assessment and evaluation of low back pain are based on questionnaires on the patient’s level of pain and discomfort. Such qualitative assessment, however, can be highly subjective and has limited accuracy in accessing the progress of rehabilitation. Moreover, the disadvantages of questionnaires are no returns (e.g. questions that are not answered), misinterpretation, and validity (e.g. the inability to check on the soundness of the answer).

By way of background, the United States Patent 6,004, 312 discloses a method and apparatus for monitoring and displaying the condition of muscles in a muscle group by the sensing and analysis of electromyographic (EMG) signals derived from a non-invasive body surface electrode array positioned close to the muscle group. According to the ‘312 patent, electronic apparatus conditions the EMG signals and is programmed to survey the electrode array simultaneously to provide a description of the activity of individual muscles in the muscle group at that point in time. The description is displayed on a video monitor or the like, juxtaposed over a display of normal muscle anatomy, with differences being emphasized by color enhancement. In the ‘312 patent, the electrode pad is particularly suited for the lower back muscle groups and may be retained in position by a lumbar support belt having a pad molded to the contours of the human spine.

It would, therefore, be advantageous to provide a solution that would overcome the deficiencies of the prior art by providing an improved system and method for monitoring a progression of the low back pain rehabilitation in a real time manner. Although there are systems and methods for the same in the prior art, for many practical purposes, there is still considerable room for improvement.

SUMMARY OF THE INVENTION

The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This summary is not an extensive overview of the invention. Its sole purpose is to present some concepts of the invention in a simplified form as a prelude to the more detailed description that is presented later.

Accordingly, the present invention provides a system for real-time monitoring a progression of low back pain rehabilitation of a subject.

The system of the present invention may be characterized by a wearable electromyography (EMG) assembly comprising a plurality of detection electrodes deployable on erector spinae muscles at a lumbar region of vertebrae L4 and L5, a signal detection module, an acquisition and transmission module and an inertia measurement module, wherein the signal detection module comprises an instrumentation amplifier, a high pass filter, a low pass filter and a pre-amplifier that are configured to condition an EMG signal detected by the said plurality of detection electrodes, wherein the acquisition and transmission module comprises a microcontroller with an analog-to-digital converter that is configured to convert the said EMG signal to a digital EMG signal, wherein the acquisition and transmission module comprises a communication module that is configured to enable wireless transmission of the said digital EMG signal, wherein the inertia measurement module comprises an accelerometer, a magnetometer and a gyroscope configured for providing an inertia signal to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position, the inertia signal comprises data on motion and orientation for the same; and a monitoring and reporting unit deployed on a computing device configured for generating a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject, wherein the monitoring and reporting unit determines, based on the digital EMG signal and the inertia signal received thereof, a flexion relaxation ratio (FRR) and an extension relaxation ratio (ERR) associated with the said erector spinae muscles, and compares the same against that of a historical data to determine the said rate of improvement or deterioration, wherein the FRR is a ratio of a maximum root mean square during a flexion of the erector spinae muscles to an average root mean square during a full flexion of the erector spinae muscles, wherein the ERR is a ratio of a maximum root mean square during an extension of the erector spinae muscles to the average root mean square during a full flexion of the erector spinae muscles, wherein the monitoring and reporting unit comprises an Internet-of-Things, loT, platform executable on a client device configured for displaying the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof, wherein the loT platform is engaged to a cloud server over a wireless communication network for connection with a third-party platform.

Preferably, the inertia measurement module is connected to the microcontroller for conversion of the inertia signal to an equivalent digital inertia signal.

Preferably, the inertia measurement module is integrally incorporated with the plurality of detection electrodes thereof.

Preferably, the wearable EMG assembly comprises a wearable patch attachable to a body part of the lumbar region thereof. Preferably, the accelerometer is a 3-axes accelerometer sensor which measures acceleration associated with the erector spinae muscle during the bending along three orthogonal axes.

Preferably, the magnetometer measures an intensity of a present magnetic fields associated with the erector spinae muscle thereof.

Preferably, the gyroscope detects rotational motion of the erector spinae muscle during the bending along three orthogonal axes.

In accordance with another aspect of the present invention, there is provided a method for real-time monitoring a progression of low back pain rehabilitation of a subject.

The method of the present invention may be characterized by the steps of deploying a plurality of detection electrodes of a wearable EMG assembly on erector spinae muscles at a lumbar region of vertebrae L4 and L5; conditioning, by a signal detection module, an EMG signal detected by the said plurality of detection electrodes, wherein the signal detection module comprises an instrumentation amplifier, a high pass filter, a low pass filter and a pre-amplifier; converting, by an acquisition and transmission module, the said EMG signal to a digital EMG signal, wherein the acquisition and transmission module comprises a microcontroller with an analog-to-digital converter; enabling, by the acquisition and transmission module, wireless transmission of the said digital EMG signal, wherein the acquisition and transmission module comprises a communication module; providing, by an inertia measurement module, an inertia signal detected thereof to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position, the inertia signal comprises data on motion and orientation for the same, wherein the inertia measurement module comprises an accelerometer, a magnetometer and a gyroscope; and generating, by a monitoring and reporting unit deployed on a computing device, a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject, including determining, based on the digital EMG signal and the inertia signal received thereof, a flexion relaxation ratio (FRR) and an extension relaxation ratio (ERR) associated with the said erector spinae muscles; and comparing the FRR and the ERR against that of a historical data to determine the said rate of improvement or deterioration, wherein the FRR is a ratio of a maximum root mean square during a flexion of the erector spinae muscles to an average root mean square during a full flexion of the erector spinae muscles, wherein the ERR is a ratio of a maximum root mean square during an extension of the erector spinae muscles to the average root mean square during a full flexion of the erector spinae muscles, wherein the monitoring and reporting unit comprises an Internet-of-Things (loT) platform executable on a client device configured for displaying the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof, wherein the loT platform is engaged to a cloud server over a wireless communication network for connection with a third- party platform.

The foregoing and other objects, features, aspects and advantages of the present invention will become better understood from a careful reading of a detailed description provided herein below with appropriate reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the invention and many of the attendant advantages thereof will be readily as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:

Figure 1 is a schematic diagram of a system for real-time monitoring a progression of low back pain rehabilitation of a subject according to one embodiment of the present invention;

Figure 2 illustrates the system of Figure 1 applied to the subject according to one embodiment of the present invention;

Figure 3 is a flow diagram of method for real-time monitoring a progression of low back pain rehabilitation of a subject according to one embodiment of the present invention; Figure 4 is an illustration of a set of graphical user interfaces of the system of Figure 1 on a computing device according to one embodiment of the present invention;

Figures 5 and 5A respectively show another graphical user interface prepared for a preliminary analysis and a set of plots derived from digital EMG signal thereof according to one embodiment of the present invention; and

Figure 6 is an illustration of an loT platform connecting the user/patient to a cloud server and a hospital/clinic portal according to one embodiment of the present invention.

It is noted that the drawings may not be to scale. The drawings are intended to depict only typical aspects of the invention, and therefore should not be considered as limiting the scope of the invention. In the drawings, like numberings represent like elements between the drawings.

DETAILED DESCRIPTION OF THE INVENTION

According to one preferred embodiment, the present invention discloses a system and method for real-time monitoring of progression of low back pain rehabilitation of a subject, which can be used and maintained in a highly specific and compact, cost-effective, quick and simple manner, without the use of complicated and sophisticated components or parts. Advantageously, the system of the present invention is non-invasive, user-friendly, robust, efficient, and economical. It can be used by subjects or patients, physiotherapists, and clinicians with low technical expertise.

The system of the present invention preferably comprises a wearable electromyography (EMG) assembly 100 and a monitoring and reporting unit 200, as schematically shown in Figure 1 . Essentially, the subject dons the wearable EMG assembly 100 and follows on a set of screen instructions deployed on the monitoring and reporting unit 200 for obtaining the progression of his or her low back pain rehabilitation. Figure 2 provide an illustration of the said system when is applied to the subject. Preferably, the wearable EMG assembly 100 comprises a plurality of detection or surface electrodes 101a, 101 b, a reference electrode, a signal detection module 102, an acquisition and transmission module 103, and an inertia measurement module 104. The plurality of detection electrodes 101a, 101b is preferably deployed or placed on or about erector spinae muscles at a lumbar region of vertebrae L4 and L5 of the subject. The lumbar region is preferably defined by the lower back which starts below the ribcage. A proper positioning of the said plurality of detection electrodes 101a, 101b with respect to the underlying erector spinae muscles is crucial due to the influence of electrode position on EMG signal’s spectra. By positioning these detection electrodes 101a, 101 b on the skin above the surface of the erector spinae muscles, the wearable EMG assembly 100 can gain a resultant bioelectric activity associated thereof in the form of an EMG signal. The detection or surface electrodes may be fabricated from an electrode material selected from a group comprising Ag-AgCI, Au, metallic nanomaterials, and carbon- based nanomaterials.

The reference electrode of the wearable EMG assembly 100 is positioned at another location on the subject, i.e. at the right leg, to acquire a reference signal to the said EMG signal. It is preferred that the reference electrode is made of the same material as that of the said detection electrodes 101a, 101 b.

In one embodiment, an adhesive layer such as a foam tape or a conductive gel may be disposed at an adhesion surface of the said detection electrodes 101a, 101b and of the said reference electrode. The adhesive layer or patch preferably holds the said detection electrodes 101a, 101b and the said reference electrode securely against the subject’s skin surface. It can be used to complement the adhesion property and signal acquisition performance of the subject’s skin to ensure the practical level of sensor capabilities.

The signal detection module 102 is preferably configured to condition the EMG signal detected by the said plurality of detection electrodes 101a, 101b. The signal detection module 102 preferably comprises an instrumentation amplifier 102a, a high pass filter 102b, a low pass filter 102c and a pre-amplifier 102d, and a signal generator 102e. The instrumentation amplifier 102a is connected to the plurality of detection electrodes 101a, 101b through a protection circuit. The reference electrode is connected to the instrumentation amplifier 102a through a right leg driver circuit. The high pass filter 102b connects the instrumentation amplifier 102a to the low pass filter 102c. The low pass filter 102c is connected to the pre-amplifier 102d which is connected to the signal generator 102e.

In one embodiment, the protection circuit comprises an EMG protection control unit to provide an emergency stop mechanism or a reset function. It is preferred that the protection circuit is activated when the EMG signal or input detected by the detection electrodes 101a, 101 b thereof becomes low.

The instrumentation amplifier 102a is configured to be responsive to the reference electrode thereof to produce a sensed biopotential EMG signal. It is preferred that the instrumentation amplifier senses a differential analog EMG signal across the detection electrodes 101a, 101b and the reference electrode.

The high pass filter 102b, upon receiving the sensed biopotential EMG signal, separates the EMG signal from other amplified signals amplified by the said instrumentation amplifier 102a. It is preferred that the high pass filter 102b comprises a predefined cut off frequency. It only accepts signals with frequencies above the said cut off frequency. For instance, the high pass filter 102b discriminates and separates the EMG signals from other signals which have lower frequencies.

The low pass filter 102c may be configured to smoothing fluctuation in the EMG signals. The low pass filter 102c preferably separates the amplified EMG signals (received from the high pass filter 102b thereof) from the other signals as amplified by the instrumentation amplifier 102a and passes only the EMG signals to the pre-amplifier 102d. The low pass filter 102c has a predefined cut off frequency and only accepts signals with frequencies below the said cut off frequency. For instance, the low pass filter 102c discriminates and separates the EMG signals from other signals which have higher frequencies.

The pre-amplifier 102d receives the EMG signals from the said low pass filter 102c and pre-amplifies the same. The pre-amplifier 102d preferably enhances the information of the EMG signals before subjecting the EMG signals to the signal generator 102e. The signal generator 102e is configured to prepare the EMG signals, which are analog EMG signals, for transmission to the acquisition and transmission module 103 for analog digital conversion.

The acquisition and transmission module 103 preferably comprises a microcontroller 103a with an analog-to-digital converter, and a communication module 103b. The microcontroller 103 is configured to convert the EMG signal received from the signal generator 102e of the signal detection module 102 to a digital EMG signal, which is assisted by the said analog-to-digital converter. It is preferred that the analog-to-digital converter is internally integrated with the microcontroller 103a.

The communication module 103b is configured to enable wireless transmission of the digital EMG signal processed by the microcontroller 103a thereof to the monitoring and reporting unit 200. The communication module 103b is preferably made discoverable and connectable on power up. It may be a transceiver module which is arranged for transmitting signals as well as receiving signals. It is preferred that the communication module 103b is a Bluetooth communication module, a wireless module, or a cable communication module.

The inertia measurement module 104 preferably comprises an accelerometer, a magnetometer and a gyroscope. It is preferred that the inertia measurement module 104 is configured for providing an inertia signal to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position. The inertia signal preferably comprises data on motion and orientation for the same. In one embodiment, the inertia measurement module 104 is connected to the microcontroller 103a for conversion of the said inertia signal to an equivalent digital inertia signal.

The accelerometer is preferably a 3-axes accelerometer sensor which measures acceleration associated with the erector spinae muscle during the bending along three orthogonal axes. It may be used to convert movement of the mass, i.e. the erector spinae muscles into a voltage signal. It is possible that more than one accelerometer is employed in the present invention. For instance, the inertia measurement module 104 may adopt two accelerometers which are placed at the two designated lumbar region L4 and L5. If one accelerometer is used, it should be mounted such that it is located centrally over the spine. The magnetometer preferably measures an intensity of a present magnetic fields associated with the erector spinae muscle thereof. The gyroscope preferably detects rotational motion of the erector spinae muscle during the bending along three orthogonal axes.

According to another embodiment, the inertia measurement module 104 is integrally incorporated with the plurality of detection electrodes 101a, 101b thereof. Wherever deemed appropriate, the inertia measurement module 104 may be manufactured as an integral or one-piece member with the said detection electrodes 101a, 101b. This may be achieved by way incorporation into a wearable patch that is attachable to a body part (e.g. the skin) of the lumbar region of the subject in a suitable manner.

The monitoring and reporting unit 200 is preferably deployed on a computing device. It can be configured for generating a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject. The monitoring and reporting unit 200 comprises a processing engine 201 having an evaluation algorithm, and a display 202 with a graphical user interface (GUI).

It is preferred that the monitoring and reporting unit 200 comprises an Internet-of-Things (loT) platform executable on a client device configured for displaying the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof. The loT platform is preferably engaged to a cloud server over a wireless communication network for connection with a third- party platform.

In one embodiment of the present invention, the monitoring and reporting unit 200 is deployed and installed as a software application on computing devices. The computing devices include but not limited to mobile devices such as handheld computers, Internet capable phone, personal digital assistants (PDAs), and laptops, as well as desktop computers from a central computer system, so that such devices and computers may run the monitoring and reporting unit 200 offline on a platform- independent framework and synchronize data with a computer system, via a standard Internet connection or other network connection. Upon receiving the digital EMG signal from the communication module 103b, the monitoring and reporting unit 200 computes and determines a flexion relaxation ratio (FRR) and an extension relaxation ratio (ERR) associated with the said erector spinae muscles. The FRR and the ERR computed thereof shall be compared against that of a historical data to determine the said rate of improvement or deterioration related to the low back pain rehabilitation.

The FRR is preferably a ratio of a maximum root mean square during a flexion of the erector spinae muscles to an average root mean square during a full flexion of the erector spinae muscles.

The ERR is preferably a ratio of a maximum root mean square during an extension of the erector spinae muscles to the average root mean square during a full flexion of the erector spinae muscles.

Flexion relaxation phenomenon (FRP) is a phenomenon where the electrical activity in the erector spinae muscles is absent during a full trunk flexion and is observed in healthy individuals. The difference in the presence of the FRP among low back pain patients is useful in the clinical assessment as it is a valuable objective clinical tool to aid in diagnosis and treatment of patients with low back pain.

In essence, the system of the present invention acquires the EMG signals from the erector spinae muscles at L4 and L5 lumbar region and wirelessly transmitted the converted EMG signals (i.e. digital EMG signals) to the computing device. The evaluation algorithm of the monitoring and reporting unit 200 utilizing the FRP is implemented to monitor the progression of low back pain rehabilitation. Figure 3 provides a flow diagram of a method for real-time monitoring the progression of low back pain rehabilitation of the subject.

The monitoring and reporting unit 200, for instance, installed in a mobile phone, can display the real time EMG signals on the display 202 of the mobile device and compute the FRR and the ERR for analysis in determining the progress of rehabilitation. Figure 4 exemplarily illustrates the GUI of the display 202. The transmitted digital EMG signals of erector spinae muscles are stored in the monitoring and reporting unit 200 (e.g. the software application) and employed to perform the FRR and the ERR calculations. The FRR and the ERR values are compared before and after interventions to analyze muscle performance. These values have been shown to increase with improvement in low back pain after rehabilitation. The system of the present invention, advantageously, will enable clinicians, physiotherapists and patients in monitoring progress of rehabilitation easily and accurately.

The FRR and the ERR are two important parameters used to quantify the progression of low back pain rehabilitation. The FRR can be calculated by dividing maximum root mean square (RMS) during flexion (MF) with average root mean square (RMS) during full flexion (AFF). The ERR can be calculated by dividing maximum root mean square (RMS) during extension (ME) with average root mean square (RMS) during full flexion (AFF). The formula of FRR and ERR can be simplified in Table 1 .

Table 1

According to one exemplary embodiment of the present invention, the EMG evaluation follows the designated protocols to yield accurate results. The duration of EMG evaluation is about 11 seconds. In the said protocol, the subject or patient is required to stand still for the first 5 seconds. Then, the patient starts to bend forward to maximum flexion (90°) from 5 to 7 second (2 seconds). The patient is required to remain at the full trunk flexion posture for 2 second which is from 7 to 9 second. Lastly, a body extension takes place and the patient is asked to return to initial standing position from 9 to 11 second (2 seconds). The protocol for 11 second EMG evaluation can be summarized in Table 2. The location or placement of the detection electrodes 101 a, 101 b is required to be determined before the EMG data acquisition. 3-channel electrodes are connected to the wearable EMG assembly 100 so that electrical signal at low back muscle can be extracted. Two electrodes 101a, 101b are attached on each end of one side erector spinae muscle in L4 and L5 vertebrae lumbar region. The reference electrode is placed on thoracic vertebrae region. The accompanying Figure 2 shows the electrode placement on the subject where two detection electrodes 101 a, 101 b are the main input for the wearable EMG assembly 100 and the other one electrode acts as a reference point, i.e. the reference electrode.

In one particular embodiment, a Bluetooth module in a mobile operating system, e.g. Android operating system, of a smartphone will be activated to allow connection of the monitoring and reporting unit 200 (i.e. the software application) to the wearable EMG assembly 100. The Android application will cease operation if Bluetooth communication is not enabled or disabled. Once the Bluetooth module is enabled, the smartphone will look for surrounding devices and pairing up with the wearable EMG assembly 100. Real time EMG signals will be transmitted wirelessly from the wearable EMG assembly 100 to the monitoring and reporting unit 200 and shall be displayed on the Android smartphone’s user screen. The transmitted data will be stored in a dedicated storage of the said smartphone, or in an external storage.

The evaluation algorithm is preferably developed to perform the FRR and the ERR evaluations. Any changes in the FRP of erector spinae muscles can be determined by way of comparing the FRR and the ERR before and after interventions. The ratio of FRR and ERR before and after intervention are calculated to visualize the rate of improvement or deterioration of low back pain progression and displayed on the smartphone screen. Different comments or consultation will be displayed with respect to different muscle performance. The physiotherapist or clinician can quantify the recovery assessment of low back pain using this clinical application, thus monitoring progress of rehabilitation easily and accurately. Table 2

The method of the present invention, as described in the preceding paragraph, preferably comprises the following steps: a. deploying a plurality of detection electrodes 101a, 101b of a wearable EMG assembly 100 on erector spinae muscles at a lumbar region of vertebrae L4 and L5; b. conditioning, by the signal detection module 102, an EMG signal detected by the said plurality of detection electrodes 101a, 101b; c. converting, by the acquisition and transmission module 103, the said EMG signal to a digital EMG signal; d. enabling, by the acquisition and transmission module 103, wireless transmission of the said digital EMG signal; e. providing, by the inertia measurement module 104, an inertia signal detected thereof to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position, the inertia signal comprises data on motion and orientation for the same; and f. generating, by the monitoring and reporting unit 200 deployed on a computing device, a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject, including: i. determining, based on the digital EMG signal and the inertia signal received thereof, an FRR and an ERR associated with the said erector spinae muscles; and ii. comparing the FRR and the ERR against that of a historical data to determine the said rate of improvement or deterioration, g. displaying, by the monitoring and reporting unit 200 through the loT platform executable on a client device, the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof; and h. transmitting the said data through the loT platform to a cloud server over a wireless communication network for connection with a third- party platform. According to one exemplary embodiment of the present invention, Figure 4 shows that the software application (or “app”) having the monitoring and reporting unit 200 installed therein works together with the wearable EMG assembly 100 of the present invention through wireless communication. The software application preferably provides the user with, but not limited to:

• START measuring function

• STOP measuring function

• Real-time posture/movement and raw EMG readings

• Low-back pain (LBP) analysis

• Progress monitoring via the progression report with the rate of improvement or deterioration

Once the app is launched, the splash screen (refer screen 1 ) with an elected logo (i.e. MyEMG being the elected name) will be displayed. The splash screen takes approximately 1 -3 seconds to proceed to screen 2. The 1 -3 seconds are required for the background user query before the app launches. After screen 1 , the measure screen will be displayed (refer screen 2). Since there is no MyEMG device connected to the phone (connection indication displayed at the top center of the screen), all the function in the measure screen is disabled. To connect to an available MyEMG device, the user has to click on the menu option (three dots on the top right corner) as pointed by A in screen 2.

Upon clicking the menu option, a small dialog box will appear with a list of devices to connect to (refer screen 3). Once the right MyEMG device is selected, connect to the device by clicking “CONNECT”. A successful connection to the right MyEMG device will activate the measure screen and the connection status indicator will turn to GREEN (refer screen 4). After confirming the placement of the MyEMG device on the user’s back (i.e. the body part of lumbar region) and readiness of the user to start the measurement, click on “START” (as pointed by C) to begin the measurement.

After the full measurement by the user (a full forward bending and back upright), the user must end the data recording by clicking the “STOP” button as shown in screen 5. That will lead the user to screen 6 which is the analysis screen where the latest data is analyzed, and the result will be displayed. The user can opt to save the data by clicking the “SAVE” button below (as pointed by E). This is important for patients under daily monitoring to observe their improvement trends over time. The results will be also pushed to a healthcare provider’s portal (being the registered third-party platform) through the cloud server for the healthcare provider’s reference. The term “healthcare provider" may refer to a doctor of medicine or osteopathy, podiatrist, chiropractor, nurse, nurse practitioner, nurse- midwife, physician's assistant, paramedic, combat medic, physical therapist, occupational therapist, pharmacist or a clinical social worker who is authorized to practice by the authority and performing within the scope of their practice as defined by law, or a science practitioner. The progress screen is shown in screen 7.

In one alternative embodiment of the present invention, it is desired that the monitoring and reporting unit 200 comprises a preliminary analysis module that is connected to a main analysis module (as described in the preceding paragraphs relating to the generation of progression report thereof). The preliminary analysis module is configured for conducting a preliminary analysis onto the said digital EMG signal (plotted thereof) to detect any occurrence of FRP on the user or patient. It is preferred that the preliminary analysis is conducted by way of comparing the digital EMG signal against a reference signal (or dataset) over a period of time. For instance, the digital EMG signal is compared against that of a healthy user. The comparison can be made on the basis EMG amplitude and/or angle value plotted thereof. Advantageously, the preliminary analysis can be used as a preliminary diagnosis to determine the type of LBP.

Figures 5 and 5A provide an exemplary embodiment pertaining to the preliminary analysis thereof. Accordingly, Figure 5 is a GUI of a screen showing the preliminary analysis conducted by the preliminary analysis module thereof. As shown, the screen displays a preliminary analysis result and an indication of presence of FRP.

Upon comparison against the predefined reference signal or dataset, the preliminary analysis module compares the digital EMG signal against the predefined reference signal or dataset to determine the presence of FRP associated with the user. It is preferred that the comparison is performed on the plot of EMG amplitude (denoted as sEMG amplitude in Figure 5A) between the digital EMG signal obtained thereof and the reference signal or dataset. Once the preliminary analysis is completed, a full analysis conducted by the main analysis module can be pursued by the user who is keen to obtain and observe the progression report including the rate of improvement or deterioration thereof. The full analysis is exemplarily shown in screen 7 of Figure 4.

As with the loT platform employed in the present invention, Figure 6 shows the communication architecture between the user held devices, cloud server and the physician’s monitoring portal. The present invention adopts the advantages of loT to enhance the usability and scalability of the system. It ensures faster computation and data storage in cloud server. Upon successful connection via Bluetooth or WiFi, the user taps “START” to invoke the MyEMG device (i.e. the wearable EMG assembly 100) to start measurement (see ). Once start code is received from the connected app, data of raw EMG and motion and orientation detected thereof will be transmitted to the app (see ‘2’). Based on the angular motion displacement, a completed measurement is recognized and “END” request is sent to the MyEMG device (see ‘3’). The completed measuring data is formatted and sent to the analysis computation unit (i.e. cloud microservice function) hosted in the cloud server to perform the LBP analysis (see ‘4’). The analysis results will be displayed for user’s reference (see ‘5’). Access to the user’s analysis results is provided in case the local history is deleted (see ‘6’).

When the analysis computation function at the analysis computation unit is invoked by the user’s app, the completed results are transmitted to the user’s app and saved in an encrypted database in the cloud server (see ‘A’). Upon successful computation and saving the database, a push notification is sent out to the monitoring portal to alert the physician about the new data thereof (see Έ’). The monitoring portal gives access to the physician to allow retrieval of data such as the progression report and users who are registered for his or her supervision. This is important for progress monitoring and evaluation of the user or patient (see ‘C’).

Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.

Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.

The foregoing description, for the purpose of explanation, has been described with reference to specific example embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the possible example embodiments to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The example embodiments were chosen and described in order to best explain the principles involved and their practical applications, to thereby enable others skilled in the art to best utilize the various example embodiments with various modifications as are suited to the particular use contemplated.

It will also be understood that, although the terms “first,” “second,” and so forth may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first contact could be termed a second contact, and, similarly, a second contact could be termed a first contact, without departing from the scope of the present example embodiments. The first contact and the second contact are both contacts, but they are not the same contact.

The terminology used in the description of the example embodiments herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used in the description of the example embodiments and the appended examples, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.

Claims

1. A system for real-time monitoring a progression of low back pain rehabilitation of a subject, characterized in that, the system comprising: a wearable electromyography, EMG, assembly (100) comprising a plurality of detection electrodes (101 a, 101 b) deployable on erector spinae muscles at a lumbar region of vertebrae L4 and L5, a signal detection module (102), an acquisition and transmission module (103) and an inertia measurement module (104), wherein the signal detection module (102) comprises an instrumentation amplifier (102a), a high pass filter (102b), a low pass filter (102c) and a pre amplifier (102d) that are configured to condition an EMG signal detected by the said plurality of detection electrodes (101a, 101b), wherein the acquisition and transmission module (103) comprises a microcontroller (103a) with an analog-to-digital converter that is configured to convert the said EMG signal to a digital EMG signal, wherein the acquisition and transmission module (103) comprises a communication module (103b) that is configured to enable wireless transmission of the said digital EMG signal, wherein the inertia measurement module (104) comprises an accelerometer, a magnetometer and a gyroscope configured for providing an inertia signal to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position, the inertia signal comprises data on motion and orientation for the same; and a monitoring and reporting unit (200) deployed on a computing device configured for generating a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject, wherein the monitoring and reporting unit (200) determines, based on the digital EMG signal and the inertia signal received thereof, a flexion relaxation ratio, FRR, and an extension relaxation ratio, ERR, associated with the said erector spinae muscles, and compares the same against that of a historical data to determine the said rate of improvement or deterioration, wherein the FRR is a ratio of a maximum root mean square during a flexion of the erector spinae muscles to an average root mean square during a full flexion of the erector spinae muscles, wherein the ERR is a ratio of a maximum root mean square during an extension of the erector spinae muscles to the average root mean square during a full flexion of the erector spinae muscles, wherein the monitoring and reporting unit (200) comprises an Internet- of-Things, loT, platform executable on a client device configured for displaying the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof, wherein the loT platform is engaged to a cloud server over a wireless communication network for connection with a third-party platform.

2. The system according to Claim 1 , wherein the inertia measurement module (104) is connected to the microcontroller (103a) for conversion of the inertia signal to an equivalent digital inertia signal.

3. The system according to Claim 1 , wherein the inertia measurement module (104) is integrally incorporated with the plurality of detection electrodes (101a, 101b) thereof.

4. The system according to Claim 1 , wherein the wearable EMG assembly (100) comprises a wearable patch attachable to a body part of the lumbar region thereof.

5. The system according to Claim 1 , wherein the accelerometer is a 3-axes accelerometer sensor which measures acceleration associated with the erector spinae muscle during the bending along three orthogonal axes.

6. The system according to Claim 1 , wherein the magnetometer measures an intensity of a present magnetic fields associated with the erector spinae muscle thereof.

7. The system according to Claim 1 , wherein the gyroscope detects rotational motion of the erector spinae muscle during the bending along three orthogonal axes.

8. A method for real-time monitoring a progression of low back pain rehabilitation of a subject, characterized in that, the method comprising the steps of: deploying a plurality of detection electrodes (101a, 101b) of a wearable electromyography, EMG, assembly (100) on erector spinae muscles at a lumbar region of vertebrae L4 and L5; conditioning, by a signal detection module (102), an EMG signal detected by the said plurality of detection electrodes (101a, 101b), wherein the signal detection module (102) comprises an instrumentation amplifier (102a), a high pass filter (102b), a low pass filter (102c) and a pre-amplifier (102d); converting, by an acquisition and transmission module (103), the said EMG signal to a digital EMG signal, wherein the acquisition and transmission module (103) comprises a microcontroller (103a) with an analog-to-digital converter; enabling, by the acquisition and transmission module (103), wireless transmission of the said digital EMG signal, wherein the acquisition and transmission module (103) comprises a communication module (103b); providing, by an inertia measurement module (104), an inertia signal detected thereof to determine an angular displacement associated with the said erector spinae muscle upon bending to a full flexion position, the inertia signal comprises data on motion and orientation for the same, wherein the inertia measurement module (104) comprises an accelerometer, a magnetometer and a gyroscope; and generating, by a monitoring and reporting unit (200) deployed on a computing device, a progression report including a rate of improvement or deterioration associated with the progression of low back rehabilitation of the subject, including: determining, based on the digital EMG signal and the inertia signal received thereof, a flexion relaxation ratio, FRR, and an extension relaxation ratio, ERR, associated with the said erector spinae muscles; and comparing the FRR and the ERR against that of a historical data to determine the said rate of improvement or deterioration, wherein the FRR is a ratio of a maximum root mean square during a flexion of the erector spinae muscles to an average root mean square during a full flexion of the erector spinae muscles, wherein the ERR is a ratio of a maximum root mean square during an extension of the erector spinae muscles to the average root mean square during a full flexion of the erector spinae muscles, wherein the monitoring and reporting unit (200) comprises an Internet- of-Things, loT, platform executable on a client device configured for displaying the EMG signal, the inertia signal, the FRR, the ERR, and the rate of improvement or deterioration thereof, wherein the loT platform is engaged to a cloud server over a wireless communication network for connection with a third-party platform.