WO2023053075A1 - Systems and methods for detecting motor and position patterns of patients - Google Patents

Systems and methods for detecting motor and position patterns of patients Download PDF

Info

Publication number
WO2023053075A1
WO2023053075A1 PCT/IB2022/059327 IB2022059327W WO2023053075A1 WO 2023053075 A1 WO2023053075 A1 WO 2023053075A1 IB 2022059327 W IB2022059327 W IB 2022059327W WO 2023053075 A1 WO2023053075 A1 WO 2023053075A1
Authority
WO
WIPO (PCT)
Prior art keywords
patient
predefined
movement
patterns
sensors
Prior art date
Application number
PCT/IB2022/059327
Other languages
French (fr)
Inventor
Giovanni MARESCA
Original Assignee
Human Motor Patterns S.R.L.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Human Motor Patterns S.R.L. filed Critical Human Motor Patterns S.R.L.
Publication of WO2023053075A1 publication Critical patent/WO2023053075A1/en

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1113Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1114Tracking parts of the body
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1123Discriminating type of movement, e.g. walking or running
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4082Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/486Bio-feedback
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6898Portable consumer electronic devices, e.g. music players, telephones, tablet computers
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/7455Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2505/00Evaluating, monitoring or diagnosing in the context of a particular type of medical care
    • A61B2505/09Rehabilitation or training
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches

Definitions

  • Patent Application No . 21425045 . 8 filed on October 1 st , 2021 , the entire disclosure of which is incorporated herein by reference .
  • the present invention relates , in general , to the field of physical and rehabilitation medicine and, more speci fically, to systems and methods for sensing patient position and movement patterns and correlated static and dynamic postures , as well as for detecting and correcting patient pathological patterns .
  • an aim of the present invention is to provide an innovative technical solution useful for the prevention, diagnosis and treatment of human postural dys functions .
  • This and other aims are achieved by the present invention in that it relates to a first method and a first system for sensing position and movement patterns and pathological patterns of a patient and a second method and a second system for correcting one or more predetermined pathological patterns of a patient , according to what is defined in the appended Claims .
  • Figure 1 schematically shows a system for sensing position and movement patterns of a patient and for sensing any pathological patterns of the patient according to an embodiment of a first aspect of the present invention
  • Figures 2A, 2B and 2C schematically show an example of use of the system of Figure 1 ;
  • Figure 3 schematically shows a system for correcting one or more predetermined pathological patterns of a patient according to an embodiment of a second aspect of the present invention.
  • Figures 4A, 4B and 4C schematically show an example of use of the system of Figure 3 .
  • Human postural dys functions are the cause of alterations in the physiological spatial relationships between the anatomical structures with consequent damage ( initially functional , then organic ) to the organism in multiple sites .
  • the assumption of the present invention is the possibility of recognizing the human motor patterns (HMP ) that strongly influence the postural system and therefore determine all possible postural , static and dynamic combinations , for each individual .
  • HMP human motor patterns
  • the aforesaid Human Motor Patterns can be defined as predefined patterns of performance of muscle activities " stored” /"memori zed” in the Central Nervous System, which contain a precise sequence of simultaneous muscle activations/deactivations of the human body and interact with the numerous other components of the postural system ( in addition to the musculoskeletal structure of the human being) .
  • the muscle activities thus generated are aimed at arranging the various body districts so as to achieve , in the predetermined time , what is envisaged by the pattern itsel f .
  • Static Patterns which allow maintaining over time a certain posture (defined as static ) in which the various body districts undergo minimal displacements , each of them remaining in a very narrow spatial field;
  • Dynamic Patterns which involve a continuous displacement in the space of the body districts , or part of them, involved in the motor pattern .
  • the assumption of the present invention is that the various postures adopted by the human being are the consequence of the HMPs and that only the recognition ( obj ecti fied and measurable in the various characteri zing elements ) of how, depending on these HMPs , the various parts of a subj ect ' s body arrange themselves and what forces are activated so that that arrangement remains or is modi fied, can allow them to be monitored allowing healthcare professionals to intervene on those resulting pathological ones and so signi ficantly af fecting the modi fications of pathological postures .
  • the present invention consists of two aspects that are highly dependent on each other and speci fically concern :
  • BMPD Brain Motor Patterns Detector
  • DCPP Device for Correction of Pathological Patterns
  • the DCPP allows , through customi zed programs established by the members of the rehabilitation team, through the activation of a wearable physical device connected to it , to provide for the correction of pathological patterns ; this is made possible because the DCPP proceeds with the real-time processing of the sensed patterns and produces/ implements correction feedback mechanisms , similar to a sentinel function, such as to induce the patient to adopt a correct posture during the various daily activities (ADL ) ; all this is done using innovative technologies , useful to improve the quality of li fe of the individuals and to prevent the onset of pathologies correlated to static and dynamic pathological motor patterns , through an important contribution to the correction of the same ; DCPP type devices use an innovative biofeedback system and use BMPD information for the recognition of a
  • BMPD Brain Motor Patterns Detector
  • Figure 1 shows a high- level architecture (in particular by means of a block diagram) of a system (indicated as a whole with 100) for sensing position and movement patterns (automatic and/or voluntary) of a patient and for sensing any pathological patterns of the patient according to an embodiment (absolutely non-limiting, nor binding) of said first aspect of the present invention.
  • System 100 includes:
  • processing means 102 which are connected (e.g., wired and/or wireless) to the sensors 101 to acquire the position and movement data generated by said sensors 101 and
  • processing means 102 are programmed to:
  • predefined reference digital models are conveniently determined a priori based on reference position and movement data generated by the sensors 101 (or by similar sensors) applied to, i.e. worn by, the patient during a preliminary calibration step of the system 100.
  • the processing means 102 may also be conveniently programmed to:
  • the processing means 102 can conveniently be made according to different architectural paradigms, for example they can be integrated into a single processing device arranged locally, i.e. also worn by, or applied to, the patient, or they can be integrated into a processing apparatus (e.g., a server) that is remotely arranged with respect to the patient and, therefore, to the sensors 101 and is connected to the latter by means of one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) ; or the processing means 102 can also be advantageously made by means of a cloud computing system remotely connected to the sensors 101 by one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc . ) .
  • a processing apparatus e.g., a server
  • wireless communication technologies e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.
  • processing means 102 are configured to implement one or more predefined artificial intelligence technologies, conveniently one or more machine learning techniques, to:
  • the system 100 can be advantageously used by doctors and technicians in the rehabilitation sector, subject to a preparatory and necessary interdisciplinary training course of the latter.
  • the system 100 i.e. the BMPD
  • the clinician allows the clinician to diagnose, with absolute certainty, the presence of a postural pathology concerning the motor patterns, so-called functional (therefore not correlated to an organic damage, which can be evidenced by the other diagnostic methods on the market, but to a malfunction of one or more structures caused by the pathological pattern) , providing precise information on it during the ADLs .
  • the system 100 i.e. the BMPD
  • the BMPD represents a complex and innovative diagnostic tool (hardware and software) obtained through a sophisticated pattern analysis system and the use of innovative and wearable technologies, aimed at identifying and classifying the pathological motor patterns (position and movement, automatic and voluntary) of the patient, as well as validating rehabilitation techniques (preventive and therapeutic) , the effectiveness of orthoses, aids and prostheses, and is also of help to clinicians to highlight pathological position or movement motor patterns, allowing diagnoses to date undetectable and obvious advantages for preventive medicine.
  • the system 100 i.e. the BMPD
  • the system 100 allows to diagnose postural dysfunctions, as well as to verify the effectiveness of the devices (e.g., braces, insoles, prostheses, aids and other orthoses) present on the market and used to improve the automatic patterns of the person who needs them, as well as the validity of rehabilitation techniques through objective measurements.
  • the devices e.g., braces, insoles, prostheses, aids and other orthoses
  • the system 100 i.e. the BMPD
  • the system 100 allows to sense and acquire data useful for the study of the position and movement patterns over a period of 24 hours and to identify the rehabilitation paths suitable for the specific cases, allowing to thoroughly measure the effects of the path adopted through the methodology of pattern analysis of the BMPD itself.
  • the pattern analysis methodology makes it possible to create a digital representation (or "digital twin") of the musculoskeletal structure of each individual patient, on which to apply all the measurements sensed through the BMPD tool so as to obtain multidimensional digital models relating to (conveniently representative of) the position and movement patterns adopted by the body, or by the predefined part(s) of the body being sensed, of the patient during the ADLs of the latter.
  • This reconstruction correlated with a contextual evaluation of the activity of the main muscle groups involved in these patterns (e.g. by means of surface electromyographic detections) and other parameters (e.g. force of gravity) allows to study the projects processed and stored in memory (HMP) which are, if necessary, automatically (without voluntary awareness) activated at the level of the Central Nervous System.
  • HMP memory
  • sensors temperature, blood oxygenation level check, etc.
  • blood oxygenation level check etc.
  • the system 100 i.e. the BMPD
  • the system 100 it is therefore possible to diagnose alterations caused by usual pathological patterns and to simultaneously verify the effectiveness of a rehabilitation treatment, an orthosis or an aid through an analysis of the position and movement patterns in the activities of daily living (ADL) before and after the intervention.
  • ADL daily living
  • the system 100 (i.e., the BMPD) is a valid support tool for research, prevention, diagnosis and treatment activities involving a rehabilitation intervention .
  • the system 100 i.e. the BMPD
  • wearable multi-parameter sensors can be conveniently used for sensing movement, distance, orientation and speed of the positions of points of the human body in space, which can be obtained through different technologies.
  • These sensors can be worn by having a direct contact with the skin and/or through specific accessories that simplify their positioning and use for several hours.
  • the requirements of the wearable sensors are miniaturization, compliance for application on the skin, autonomy, low absorption (duration in hours sufficient for the intended use) , connectivity, can communicate with each other and with a wearable control unit, make very accurate measurements, do not require intervention by the patient, are remotely controllable, ensure through appropriate encryption protocols the security and confidentiality of the data produced, are reusable.
  • sensors can be positioned on various parts of the body comfortably and provide important information, in real time, inherent in spatial placement, muscle (electrical) activities, temperature, blood oxygenation and more.
  • muscle (electrical) activities when used in combination with each other and interconnected with wearable tools, they can easily interact with cloud-based systems to perform structural and functional analyses of the patient, whether they are in static or dynamic mode, both at an equipped facility and during the patient's activities of daily living (ADL) .
  • ADL daily living
  • the sensors 101 may conveniently include movement sensors, accelerometers, magnetometers, surface electromyographs, frequency meters, temperature, oxygenation meters, pressure and/or strain and/or vibration sensors, noise detectors, etc.
  • software modules can be conveniently used that allow to integrate the information sensed by the sensors 101 used with virtual models representative of the musculoskeletal structure of the patient, so as to create a completely digital model of the patient's pattern, which in turn can be compared (for example, via machine learning systems) with predefined pathological patterns.
  • the processing means 102 can conveniently include different software modules, each of which is dedicated to specific functions, such as the management of digital musculoskeletal models and related patterns, calculation algorithms for decoding the data sensed by the sensors 101 and applied to the patient model, diagnostics, reporting, etc.
  • Another software module can conveniently be dedicated to the reporting of pathological motor patterns (compared to the individual characteristics of each subject) and correlated postural imbalances with qualitative and quantitative data, statistics and distribution times in the performance of ADLs .
  • Figures 2A, 2B and 2C show (particularly by means of a flowchart) an example of use of the system 100 (i.e., the BMPD) .
  • Figure 3 shows a high- level architecture (in particular by means of a block diagram) of a system (collectively referred to as 300) for correcting one or more predetermined pathological patterns of a patient according to an (absolutely non-limiting, nor binding) embodiment of said second aspect of the present invention .
  • the system 300 includes a correction device 301 (e.g., an orthosis, an aid, a prosthesis, or the like) designed to be worn by, or applied to, a patient during the ADLs of the latter to correct one or more predetermined pathological patterns of said patient.
  • a correction device 301 e.g., an orthosis, an aid, a prosthesis, or the like
  • system 300 also comprises:
  • a plurality of sensors 302 that can be conveniently integrated into the correction device 301 (as shown in Figure 3) , or not integrated into the latter, but otherwise worn by, or applied to, the patient together with the correction device 301 during the ADLs of the latter and that are configured to
  • one or more stimulation devices 303 that can be conveniently integrated into the correction device 301 (as shown in Figure 3) , or not integrated into the latter, but otherwise worn by, or applied to, the patient together with the correction device 301 during the ADLs of the latter and that are operable to provide one or more predefined stimulations to the patient;
  • processing and control means 304 which are
  • the stimulation device (s) 303 if the predetermined pathological pattern (s) persist (s) , operate the stimulation device (s) 303 so as to induce the patient to modify the position and movement patterns adopted so as not to adopt said predetermined pathological pattern (s) (realtime feed-back) .
  • processing and control means 304 are programmed to:
  • the system 100 can be conveniently used, in a preliminary step preparatory to the use of the system 300, to detect a priori said predetermined pathological pattern (s) and to determine (i.e., generate) the relative predetermined reference digital model (s) to be used in the aforesaid comparison .
  • the processing and control means 304 may conveniently be realized according to different architectural paradigms, for example they may be integrated into the correction device 301 (as shown in Figure 3) , or they may be integrated into an apparatus (e.g., a server) that is remotely arranged with respect to the patient and, therefore, to the correction device 301, to the sensors 302 and to the stimulation device (s) 303 and is connected to the latter via one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) ; or the processing and control means 304 may also be advantageously realized by means of a cloud computing system remotely connected to the sensors 302 and to the stimulation device (s) 303 by means of one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) .
  • wireless communication technologies e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.
  • processing and control means 304 are configured to implement one or more predefined artificial intelligence technologies, conveniently one or more machine learning techniques, to:
  • the system 300 i.e. the DCPP
  • the DCPP represents an innovative tool (hardware and software) and customizable for each patient for the correction of pathological patterns (mainly orthoses) , obtained through the use of innovative and wearable technologies that are useful for improving the quality of life of individuals and to prevent the onset of pathologies correlated to postural or pathological movement patterns, and to the correction of existing pathological motor patterns, through an important contribution to the "correction" of the same.
  • the interaction between the BMPD and the DCPP is important, as the former tool allows one to take a sort of multidimensional digital snapshot of the patient's pathological motor pattern, highlighting through the pattern analysis function which imbalances are sensed, allowing an intervention strategy to be set up to remedy them.
  • the DCPP provides, based on what was sensed by the BMPD, the specifications and the characteristics of the orthosis or of the aid to be made and applied to the patient to stimulate him to reprogramme his pattern .
  • the DCPP has all the data processed ad-hoc by the BMPD for the patient , so as to know exactly what he has to check during the period (ADL ) and when to intervene in order to process the type of feedback most suitable for the subj ect , which stimulates the patient to respect correct patterns ( i . e . , reset his pattern and apply a corrective pattern) .
  • the orthosis made based on the information produced by the BMPD is a customised physical-digital device , that is , not a simple prosthesis , but a device made ad-hoc for each individual patient and provided with digital intelligence and interconnected to the BMPC to inherit the corrective information and exchange the information sensed during the period in which the patient wears it (bio- feedback analysis ) .
  • the DCPPs are devices obtained through the use of innovative technologies that operate through detections , data processing and real-time postural correction feedback .
  • the aim of the DCPPs is to contribute to the correction of pathological patterns by replacing them with more functional ones , improving the quality of li fe of the individuals and preventing the onset of pathologies correlated to pathological static or dynamic postural patterns .
  • DCPPs are conveniently provided with a bio- feedback mechanism, it is appropriate to include the role of a psychologist in the multidisciplinary team that follows the patient , whose task is not only to collaborate in the reali zation of the operating software for the use of these devices , but also to veri fy the eligibility of the candidates for use , as well as to analyse with the team the progress of the therapeutic pathway during the implementation of the rehabilitation plan .
  • the DCPP management software evaluates , also through an arti ficial intelligence system, by processing the patient data and the responses recorded during the use o f the worn device, the best communication channel among the sensors in order to identify, among the perceptual tools, the one most suitable for the specific subject together with the evaluation of the type, frequency and intensity of the feedbacks .
  • wearable multi-parameter sensors can be conveniently used for sensing movement, distance, orientation and speed of the positions of points of the human body in space, which can be obtained through different technologies.
  • These sensors can be worn by having a direct contact with the skin and/or through specific accessories that simplify their positioning and use for several hours.
  • the requirements of the wearable sensors are miniaturization, compliance for application on the skin, autonomy, low absorption (duration in hours sufficient for the intended use) , connectivity, can communicate with each other and with a wearable control unit, make very accurate measurements, do not require intervention by the patient, are remotely controllable, ensure through appropriate encryption protocols the security and confidentiality of the data produced, are reusable.
  • the sensors 302 may conveniently include movement sensors, accelerometers, magnetometers, surface electromyographs, frequency meters, temperature, oxygenation meters, pressure and/or strain and/or vibration sensors, noise detectors, etc.
  • the stimulation devices 303 may conveniently include heat/vibration/cold effectors, etc.
  • processing and control means 304 From a software point of view, the processing and control means 304 :
  • the DCPP software (i.e., the processing and control means 304) is preferably of the embedded type, i.e., resident in the wearable control unit, in order to analyse and return to the BMPD the relevant bio-feedback collected in the ADL period referring to the basic positions (orthostatic, etc.) , in whatever operating condition the patient is in (e.g., absence of external data connectivity) .
  • the DCPP also has an active function, that is, to signal to the patient in real time the adoption of a "usual pathological pattern" previously identified through the BMPD and therefore known to the patient who adopts it "involuntarily” according to its own automatism (to be corrected) stimulating them to apply the new motor pattern to be taken, in addition to storing and cataloguing information on the measurements they make when they are in the coded positions.
  • Figures 4A, 4B and 4C show (in particular by means of a flow chart) an example of the use of the system 300 (i.e. DCPP) .
  • An example of a DCPP is a pelvis setup adjustment device (referred to by the Applicant as the "Pelvis Position Optimizer" - PPO) .
  • the PPO is a hardware/sof tware device aimed at correcting usual pathological patterns that involve deviations of the pelvis in the planes of the space.
  • the hardware component consists of sensors and effectors. They are connected to a device (e.g. a smartphone) that sends information from the sensors to a central server which, by processing the data compared with individual standards predetermined by the rehabilitation team together with the individual treatment plan for each subject, provides realtime feedbacks, subsequently taking into account any changes in the patterns and their persistence over time.
  • both basic components e.g., sensors, interfaces, etc.
  • both basic components e.g., sensors, interfaces, etc.
  • specially designed and manufactured for the purpose can be conveniently used .
  • the present invention exploits software programs/modules for processing the sensed parameters and for creating a 3D model of the human musculoskeletal system, as well as using speci fic algorithms necessary for the recognition and coding of patterns for the reali zation of multidimensional models of the patterns referred to each patient .
  • the aforesaid multidisciplinary team is preferably responsible for the analysis of the motor patterns , the decisions on the strategies to be implemented and the drafting of a timetable with defined obj ectives (for example , envisaging periodic checks to assess the achievement of intermediate obj ectives and/or to deal with any unforeseen events ) .

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Veterinary Medicine (AREA)
  • Pathology (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Biophysics (AREA)
  • Physiology (AREA)
  • Neurology (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Artificial Intelligence (AREA)
  • Neurosurgery (AREA)
  • Dentistry (AREA)
  • Mathematical Physics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Developmental Disabilities (AREA)
  • Fuzzy Systems (AREA)
  • Evolutionary Computation (AREA)
  • Multimedia (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

Disclosed are methods and systems for sensing position and movement patterns and pathological patterns of a patient by applying to the patient sensors (101) designed to sense the position and movement of the body, or parts of the body, during activities of daily living, determining, by a processing means (102), position and movement patterns adopted by the body, or by the parts of the body, during the activities of daily living, and analysing, by the processing means (102), the position and movement patterns to detect one or more pathological pattern of the patient. Furthermore, one or more stimulation device (303) is operable to provide one or more predefined stimulation to the patient, if it is detected that the pathological pattern persists.

Description

SYSTEMS AND METHODS FOR DETECTING MOTOR AND POSITION PATTERNS OF PATIENTS
CROSS-REFERENCE TO RELATED APPLICATIONS
This Patent Application claims priority from European
Patent Application No . 21425045 . 8 filed on October 1st, 2021 , the entire disclosure of which is incorporated herein by reference .
TECHNICAL SECTOR OF THE INVENTION
The present invention relates , in general , to the field of physical and rehabilitation medicine and, more speci fically, to systems and methods for sensing patient position and movement patterns and correlated static and dynamic postures , as well as for detecting and correcting patient pathological patterns .
STATE OF THE ART
One of the maj or problems currently encountered in the rehabilitation sector is related to the fact that :
• in the course of an individual rehabilitation proj ect , the methods used by medical specialists and technicians are operator-dependent ; and
• the results of most of the interventions carried out are not uniquely measurable .
In fact , although there are many validated assessment scales for measuring the level of motor disability, the use of the latter, although it allows the classi fication of the pathology, does not however allow the quantitative measurement of the individual disorders that characteri ze each individual patient .
The greatest di f ficulty, for the purpose of a correct functional diagnosis and veri fication of the results of the therapeutic strategies undertaken in the rehabilitation sector, has always been the obj ectivi zation of the state of position and movement of the multiple parts that make up the human body, due to the very numerous and sophisticated structures that compose it as well as the complexity of the functioning of the postural system (posture study) .
In recent years , numerous systems have been developed in order to provide instruments ( e . g . , cameras with re flective markers , platforms , pressure and position sensors , surface electromyographs , etc . ) to movement study laboratories , also for sports-athletic purposes , through the graphic analysis of the subj ect ' s biomechanics , which however does not allow a detailed analysis of adequate and accurate parameters correlated to the subj ect ' s postural and/or pathological characteristics .
Other instruments are used experimentally for the biomechanical analysis of speci fic parts of the body, but such measurements are only possible in a controlled environment and using expensive equipment .
More generally speaking, all the systems known to date necessarily require the use of a fixed station ( i . e . they require non-transportable equipment ) and therefore allow to study only the static and dynamic postures , adopted in the lab and not in activities of daily living (ADL ) , where the exclusive study in a controlled environment represents a strong limitation, not allowing to sense these parameters during the usual ADL .
OBJECT AND SUMMARY OF THE INVENTION
In light of what has been explained above , the Applicant has felt the need to conduct a very thorough research in order to develop an innovative technical solution capable of overcoming, or at least alleviating, the aforesaid problems of systems and techniques of a known type .
More speci fically, by virtue of the great experience accumulated over many years of professional activity carried out in the field of physical and rehabilitation medicine as a specialist physiatrist , the inventor felt the need to develop an innovative technical solution useful for the prevention, diagnosis and treatment of human postural dys functions .
Therefore , an aim of the present invention is to provide an innovative technical solution useful for the prevention, diagnosis and treatment of human postural dys functions .
This and other aims are achieved by the present invention in that it relates to a first method and a first system for sensing position and movement patterns and pathological patterns of a patient and a second method and a second system for correcting one or more predetermined pathological patterns of a patient , according to what is defined in the appended Claims .
BRIEF DESCRIPTION OF THE DRAWINGS
In order to better understand the present invention, some preferred embodiments , provided for merely exemplary and non-limiting purposes will now be shown with reference to the enclosed drawings (not in a scale ) , wherein :
• Figure 1 schematically shows a system for sensing position and movement patterns of a patient and for sensing any pathological patterns of the patient according to an embodiment of a first aspect of the present invention;
• Figures 2A, 2B and 2C schematically show an example of use of the system of Figure 1 ;
• Figure 3 schematically shows a system for correcting one or more predetermined pathological patterns of a patient according to an embodiment of a second aspect of the present invention; and
• Figures 4A, 4B and 4C schematically show an example of use of the system of Figure 3 .
DETAILED DESCRIPTION OF POSSIBLE EMBODIMENTS OF THE INVENTION
The following description is provided to enable a person skilled in the art to make and use the invention . Various modi fications to the embodiments set forth will be immediately clear to the persons s killed in the art and the general principles herein disclosed may be applied to other embodiments and applications without , however, departing from the protection scope of the present invention as defined in the enclosed Claims .
Therefore , the present invention should not be understood as limited to the sole embodiments described and shown, but it must be given the widest scope of protection in accordance with the characteristics defined in the appended Claims .
Human postural dys functions are the cause of alterations in the physiological spatial relationships between the anatomical structures with consequent damage ( initially functional , then organic ) to the organism in multiple sites .
The assumption of the present invention is the possibility of recogni zing the human motor patterns (HMP ) that strongly influence the postural system and therefore determine all possible postural , static and dynamic combinations , for each individual .
The aforesaid Human Motor Patterns (HMP ) can be defined as predefined patterns of performance of muscle activities " stored" /"memori zed" in the Central Nervous System, which contain a precise sequence of simultaneous muscle activations/deactivations of the human body and interact with the numerous other components of the postural system ( in addition to the musculoskeletal structure of the human being) . The muscle activities thus generated are aimed at arranging the various body districts so as to achieve , in the predetermined time , what is envisaged by the pattern itsel f .
There are two main types of patterns :
1 ) Static Patterns , which allow maintaining over time a certain posture ( defined as static ) in which the various body districts undergo minimal displacements , each of them remaining in a very narrow spatial field;
2 ) Dynamic Patterns , which involve a continuous displacement in the space of the body districts , or part of them, involved in the motor pattern .
The assumption of the present invention is that the various postures adopted by the human being are the consequence of the HMPs and that only the recognition ( obj ecti fied and measurable in the various characteri zing elements ) of how, depending on these HMPs , the various parts of a subj ect ' s body arrange themselves and what forces are activated so that that arrangement remains or is modi fied, can allow them to be monitored allowing healthcare professionals to intervene on those resulting pathological ones and so signi ficantly af fecting the modi fications of pathological postures .
Thanks to the possibility of acquiring this information in a structured, organised and systematic manner, it is possible to sense all the deviations from the individual standards ( i . e . , balance setup of the individual subj ect analysed) establi shed by the specialist doctor, producing a digital format of the "position patterns" and "movement patterns" in the ADLs . From the scienti fic evidence in the literature it can be noted that , to date , only lab case studies and experiments in controlled environments are known, but not the creation of a digital system capable of supporting the rehabilitation specialist in the three work step (prevention, diagnosis and treatment ) .
The present invention consists of two aspects that are highly dependent on each other and speci fically concern :
1 ) a complex and innovative diagnostic tool (hardware and software ) cal led by the Applicant "Brain Motor Patterns Detector" (BMPD) , aimed at the identi fication and classi fication of the motor patterns of a patient , responsible for the various postures ( static and/or dynamic, automatic and/or voluntary) he adopts during the activities of daily living (ADL ) , and at the validation of the rehabilitation techniques (preventive and therapeutic ) , the ef fectiveness of orthoses , aids and prostheses ; this tool (BMPD) was also designed to support clinicians in highlighting position and/or movement pathological patterns , thus allowing the automatic recognition of postural dys functions with the related distress areas af fected; the BMPD records and analyses the patient ' s motor patterns , disclosing their characteristics during ADLs , highlighting and quanti fying their alterations , thus allowing to diagnose postural dys functions also supported by minor functional disorders ; the latter, largely widespread in the population and rarely diagnosed, if not appropriately corrected, can be a cause of numerous anatomical pathologies (with anatomical damage ) over time ;
2 ) an innovative tool (hardware and software ) and customi zable for each patient for the correction of pathological patterns (mainly orthoses ) , called by the Applicant "Device for Correction of Pathological Patterns" ( DCPP ) ; the DCPP allows , through customi zed programs established by the members of the rehabilitation team, through the activation of a wearable physical device connected to it , to provide for the correction of pathological patterns ; this is made possible because the DCPP proceeds with the real-time processing of the sensed patterns and produces/ implements correction feedback mechanisms , similar to a sentinel function, such as to induce the patient to adopt a correct posture during the various daily activities (ADL ) ; all this is done using innovative technologies , useful to improve the quality of li fe of the individuals and to prevent the onset of pathologies correlated to static and dynamic pathological motor patterns , through an important contribution to the correction of the same ; DCPP type devices use an innovative biofeedback system and use BMPD information for the recognition of a pathological pattern; in addition, the use of non-invasive , miniaturi zed and wearable type technologies allows the system to be used for a wide range of patients, as well as to be applied for numerous pathologies.
1. Brain Motor Patterns Detector (BMPD)
For a better understanding of the first aspect of the present invention (i.e., the BMPD) , Figure 1 shows a high- level architecture (in particular by means of a block diagram) of a system (indicated as a whole with 100) for sensing position and movement patterns (automatic and/or voluntary) of a patient and for sensing any pathological patterns of the patient according to an embodiment (absolutely non-limiting, nor binding) of said first aspect of the present invention.
As shown in Figure 1, System 100 includes:
• a plurality of sensors 101 designed to be worn by, or applied to, a patient during the ADLs of the latter and configured to
- continuously sense quantities relating to the patient's posture, i.e. to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during the ADLs of the latter and
- generate, based on the sensed quantities, corresponding position and movement data; and
• processing means 102 which are connected (e.g., wired and/or wireless) to the sensors 101 to acquire the position and movement data generated by said sensors 101 and
- programmed to
- perform a predefined processing of the position and movement data acquired determining, based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the ADLs of the latter (e.g. orthostatic, seated, clinostatic posture, etc.) and - analyse the position and movement patterns determined to detect any pathological patterns of the patient.
Preferably, the processing means 102 are programmed to:
• perform the predefined processing determining (i.e., generating) , based on the acquired position and movement data, multidimensional digital models relating to (conveniently representative of) the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the ADLs of the latter; and
• detect any patient pathological patterns based on a comparison between the determined multidimensional digital models and predefined reference digital models relating to
(conveniently representative of) reference position and movement patterns of the patient, wherein said predefined reference digital models are conveniently determined a priori based on reference position and movement data generated by the sensors 101 (or by similar sensors) applied to, i.e. worn by, the patient during a preliminary calibration step of the system 100.
The processing means 102 may also be conveniently programmed to:
• recognize imbalances associated with the pathological patterns detected and identify related distress areas;
• generate quantitative and qualitative descriptive reports of the imbalances found in the various positions adopted (e.g., mono or bipodalic, seated, clinostatic, etc . ) ; and
• produce reports relating to the pathological patterns adopted over 24 hours (indicating, conveniently, type, duration, frequency, etc.) with an indication of the related distress areas resulting from said pathological patterns.
The processing means 102 can conveniently be made according to different architectural paradigms, for example they can be integrated into a single processing device arranged locally, i.e. also worn by, or applied to, the patient, or they can be integrated into a processing apparatus (e.g., a server) that is remotely arranged with respect to the patient and, therefore, to the sensors 101 and is connected to the latter by means of one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) ; or the processing means 102 can also be advantageously made by means of a cloud computing system remotely connected to the sensors 101 by one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc . ) .
Preferably, the processing means 102 are configured to implement one or more predefined artificial intelligence technologies, conveniently one or more machine learning techniques, to:
• perform the predefined processing of the position and movement data acquired and other types of parameters (body temperature, oxygenation, etc.) ;
• determine the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the ADLs of the latter;
• analyse the determined position and movement patterns; and
• detect any pathological patterns of the patient.
The system 100 can be advantageously used by doctors and technicians in the rehabilitation sector, subject to a preparatory and necessary interdisciplinary training course of the latter.
It is important to point out that the system 100 (i.e. the BMPD) allows the clinician to diagnose, with absolute certainty, the presence of a postural pathology concerning the motor patterns, so-called functional (therefore not correlated to an organic damage, which can be evidenced by the other diagnostic methods on the market, but to a malfunction of one or more structures caused by the pathological pattern) , providing precise information on it during the ADLs .
It must be reiterated that, to date, there are no other diagnostic tools on the market capable of sensing a functional pathology except in a controlled environment (e.g., in a lab) and limited to some known and evident dysfunctions, with all the consequent understandable limitations .
In the light of what has been explained above, the system 100 (i.e. the BMPD) represents a complex and innovative diagnostic tool (hardware and software) obtained through a sophisticated pattern analysis system and the use of innovative and wearable technologies, aimed at identifying and classifying the pathological motor patterns (position and movement, automatic and voluntary) of the patient, as well as validating rehabilitation techniques (preventive and therapeutic) , the effectiveness of orthoses, aids and prostheses, and is also of help to clinicians to highlight pathological position or movement motor patterns, allowing diagnoses to date undetectable and obvious advantages for preventive medicine.
More in detail, the system 100 (i.e. the BMPD) allows to diagnose postural dysfunctions, as well as to verify the effectiveness of the devices (e.g., braces, insoles, prostheses, aids and other orthoses) present on the market and used to improve the automatic patterns of the person who needs them, as well as the validity of rehabilitation techniques through objective measurements.
In particular, the system 100 (i.e. the BMPD) allows to sense and acquire data useful for the study of the position and movement patterns over a period of 24 hours and to identify the rehabilitation paths suitable for the specific cases, allowing to thoroughly measure the effects of the path adopted through the methodology of pattern analysis of the BMPD itself.
In fact, the pattern analysis methodology makes it possible to create a digital representation (or "digital twin") of the musculoskeletal structure of each individual patient, on which to apply all the measurements sensed through the BMPD tool so as to obtain multidimensional digital models relating to (conveniently representative of) the position and movement patterns adopted by the body, or by the predefined part(s) of the body being sensed, of the patient during the ADLs of the latter. This results in a precise multidimensional virtual reconstruction of the model referring to the individual patient analysed (positions, distances, angles, forces, etc. ) , inclusive of all the anatomical components referred to the voluntary or automatic motor patterns of position and movement. This reconstruction, correlated with a contextual evaluation of the activity of the main muscle groups involved in these patterns (e.g. by means of surface electromyographic detections) and other parameters (e.g. force of gravity) allows to study the projects processed and stored in memory (HMP) which are, if necessary, automatically (without voluntary awareness) activated at the level of the Central Nervous System.
In addition, other types of sensors (temperature, blood oxygenation level check, etc.) can also be conveniently used which are useful in order to verify the effects of the different patterns on other organs and/or apparatus.
With the system 100 (i.e. the BMPD) it is therefore possible to diagnose alterations caused by usual pathological patterns and to simultaneously verify the effectiveness of a rehabilitation treatment, an orthosis or an aid through an analysis of the position and movement patterns in the activities of daily living (ADL) before and after the intervention.
Therefore, the system 100 (i.e., the BMPD) is a valid support tool for research, prevention, diagnosis and treatment activities involving a rehabilitation intervention . In addition, it is important to point out the fact that the system 100 (i.e. the BMPD) contributes, with its use in the context of an individual rehabilitation project of a patient, to making measurable over time the results obtained by a patient and multidisciplinary team, preferably composed of a doctor specialising in physiatrics, a physiotherapist, an orthopaedic technician, a psychologist and a biomedical engineer or specialized technician.
For the realization of the system 100, in particular for the realization of the sensors 101, wearable multi-parameter sensors can be conveniently used for sensing movement, distance, orientation and speed of the positions of points of the human body in space, which can be obtained through different technologies. These sensors can be worn by having a direct contact with the skin and/or through specific accessories that simplify their positioning and use for several hours. The requirements of the wearable sensors are miniaturization, compliance for application on the skin, autonomy, low absorption (duration in hours sufficient for the intended use) , connectivity, can communicate with each other and with a wearable control unit, make very accurate measurements, do not require intervention by the patient, are remotely controllable, ensure through appropriate encryption protocols the security and confidentiality of the data produced, are reusable.
In fact, in recent years, advances in materials and electronics have produced a wide range of sensors and other sensing systems/devices that are increasingly efficient and economical than ever before. The various types of sensors can be positioned on various parts of the body comfortably and provide important information, in real time, inherent in spatial placement, muscle (electrical) activities, temperature, blood oxygenation and more. In addition, when used in combination with each other and interconnected with wearable tools, they can easily interact with cloud-based systems to perform structural and functional analyses of the patient, whether they are in static or dynamic mode, both at an equipped facility and during the patient's activities of daily living (ADL) .
Purely by way of example, but in no way limiting nor binding, the sensors 101 may conveniently include movement sensors, accelerometers, magnetometers, surface electromyographs, frequency meters, temperature, oxygenation meters, pressure and/or strain and/or vibration sensors, noise detectors, etc.
Furthermore, for the realization of the system 100, in particular for the realization of the processing means 102, software modules can be conveniently used that allow to integrate the information sensed by the sensors 101 used with virtual models representative of the musculoskeletal structure of the patient, so as to create a completely digital model of the patient's pattern, which in turn can be compared (for example, via machine learning systems) with predefined pathological patterns.
More in detail, the processing means 102 can conveniently include different software modules, each of which is dedicated to specific functions, such as the management of digital musculoskeletal models and related patterns, calculation algorithms for decoding the data sensed by the sensors 101 and applied to the patient model, diagnostics, reporting, etc. Another software module can conveniently be dedicated to the reporting of pathological motor patterns (compared to the individual characteristics of each subject) and correlated postural imbalances with qualitative and quantitative data, statistics and distribution times in the performance of ADLs .
Moreover, in order to better interpret the patterns and reduce the margins of error of the system 100, it may be conveniently provided for the use of a specific agenda to be filled in by the patient in the event that abnormal situations occur that may affect the patterns (for example, wearing a backpack, carrying a weight, etc.) , with annotation of the start and end time of the action.
Figures 2A, 2B and 2C show (particularly by means of a flowchart) an example of use of the system 100 (i.e., the BMPD) .
In particular, the steps of use of the system 100 (i.e. of the BMPD) shown in Figures 2A-2C (and progressively numbered from 201 to 218) are absolutely self-explanatory and immediately understandable by any technician in the field, so they will not be described in detail here.
2. Device for Correction of Pathological Patterns (DCPP)
For a better understanding of the second aspect of the present invention (i.e., the DCPP) , Figure 3 shows a high- level architecture (in particular by means of a block diagram) of a system (collectively referred to as 300) for correcting one or more predetermined pathological patterns of a patient according to an (absolutely non-limiting, nor binding) embodiment of said second aspect of the present invention .
As shown in Figure 3, the system 300 includes a correction device 301 (e.g., an orthosis, an aid, a prosthesis, or the like) designed to be worn by, or applied to, a patient during the ADLs of the latter to correct one or more predetermined pathological patterns of said patient.
In addition, the system 300 also comprises:
• a plurality of sensors 302 that can be conveniently integrated into the correction device 301 (as shown in Figure 3) , or not integrated into the latter, but otherwise worn by, or applied to, the patient together with the correction device 301 during the ADLs of the latter and that are configured to
- continuously sense quantities relating to the patient's posture, i.e. to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during the ADLs of the latter and while he is wearing said correction device 301 and
- generate, based on the sensed quantities, corresponding position and movement data;
• one or more stimulation devices 303 that can be conveniently integrated into the correction device 301 (as shown in Figure 3) , or not integrated into the latter, but otherwise worn by, or applied to, the patient together with the correction device 301 during the ADLs of the latter and that are operable to provide one or more predefined stimulations to the patient; and
• processing and control means 304 which are
- connected (e.g., wired and/or wireless) to the stimulation device (s) 303 and to the sensors 302 to acquire the position and movement data generated by said sensors 302 and
- programmed to
- perform a predefined processing of the position and movement data acquired determining, based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the ADLs of the latter and while he is wearing said correction device (301) ,
- detect, based on the determined position and movement patterns, whether the predetermined pathological pattern (s) persist (s) and,
- if the predetermined pathological pattern (s) persist (s) , operate the stimulation device (s) 303 so as to induce the patient to modify the position and movement patterns adopted so as not to adopt said predetermined pathological pattern (s) (realtime feed-back) .
Preferably, the processing and control means 304 are programmed to:
• perform the predefined processing determining (i.e., generating) , based on the acquired position and movement data, multidimensional digital models relating to (conveniently representative of) the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the ADLs of the latter and while he is wearing said correction device 301; and
• detect whether the predetermined pathological pattern (s) persist (s) based on a comparison between the determined multidimensional digital models and one or more predetermined reference digital models relating to (conveniently representative of) said predetermined pathological pattern (s) .
The system 100 can be conveniently used, in a preliminary step preparatory to the use of the system 300, to detect a priori said predetermined pathological pattern (s) and to determine (i.e., generate) the relative predetermined reference digital model (s) to be used in the aforesaid comparison .
The processing and control means 304 may conveniently be realized according to different architectural paradigms, for example they may be integrated into the correction device 301 (as shown in Figure 3) , or they may be integrated into an apparatus (e.g., a server) that is remotely arranged with respect to the patient and, therefore, to the correction device 301, to the sensors 302 and to the stimulation device (s) 303 and is connected to the latter via one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) ; or the processing and control means 304 may also be advantageously realized by means of a cloud computing system remotely connected to the sensors 302 and to the stimulation device (s) 303 by means of one or more wireless communication technologies (e.g., 3G, 4G, 5G mobile telephony technologies, Wi-Fi technology, etc.) .
Preferably, the processing and control means 304 are configured to implement one or more predefined artificial intelligence technologies, conveniently one or more machine learning techniques, to:
• perform the predefined processing of the position and movement data acquired;
• determine the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient;
• analyse the determined position and movement patterns; and
• detect whether the predetermined pathological pattern(s) persist(s) .
Conveniently, based on the position and movement data provided by the sensors 302 following activation of various stimulation devices, it is possible to identify the most suitable and/or most efficient stimulation device (s) for stimulating the patient so that he does not adopt the predetermined pathological pattern (s) .
In light of what has been explained above, the system 300 (i.e. the DCPP) represents an innovative tool (hardware and software) and customizable for each patient for the correction of pathological patterns (mainly orthoses) , obtained through the use of innovative and wearable technologies that are useful for improving the quality of life of individuals and to prevent the onset of pathologies correlated to postural or pathological movement patterns, and to the correction of existing pathological motor patterns, through an important contribution to the "correction" of the same.
The interaction between the BMPD and the DCPP is important, as the former tool allows one to take a sort of multidimensional digital snapshot of the patient's pathological motor pattern, highlighting through the pattern analysis function which imbalances are sensed, allowing an intervention strategy to be set up to remedy them. The DCPP provides, based on what was sensed by the BMPD, the specifications and the characteristics of the orthosis or of the aid to be made and applied to the patient to stimulate him to reprogramme his pattern . Therefore , the DCPP has all the data processed ad-hoc by the BMPD for the patient , so as to know exactly what he has to check during the period (ADL ) and when to intervene in order to process the type of feedback most suitable for the subj ect , which stimulates the patient to respect correct patterns ( i . e . , reset his pattern and apply a corrective pattern) . It goes without saying that the orthosis made based on the information produced by the BMPD is a customised physical-digital device , that is , not a simple prosthesis , but a device made ad-hoc for each individual patient and provided with digital intelligence and interconnected to the BMPC to inherit the corrective information and exchange the information sensed during the period in which the patient wears it (bio- feedback analysis ) . In fact , the DCPPs are devices obtained through the use of innovative technologies that operate through detections , data processing and real-time postural correction feedback .
In particular, the aim of the DCPPs is to contribute to the correction of pathological patterns by replacing them with more functional ones , improving the quality of li fe of the individuals and preventing the onset of pathologies correlated to pathological static or dynamic postural patterns .
As far as said DCPPs are concerned, since the latter are conveniently provided with a bio- feedback mechanism, it is appropriate to include the role of a psychologist in the multidisciplinary team that follows the patient , whose task is not only to collaborate in the reali zation of the operating software for the use of these devices , but also to veri fy the eligibility of the candidates for use , as well as to analyse with the team the progress of the therapeutic pathway during the implementation of the rehabilitation plan .
The DCPP management software evaluates , also through an arti ficial intelligence system, by processing the patient data and the responses recorded during the use o f the worn device, the best communication channel among the sensors in order to identify, among the perceptual tools, the one most suitable for the specific subject together with the evaluation of the type, frequency and intensity of the feedbacks .
Therefore, it is important to carefully evaluate the candidates for the use of these devices, as well as to codify the steps of the implementation of rehabilitation interventions in which these devices are inserted, from the detection of the imbalance (pathological pattern) , to the physiotherapy treatment and to the possible use of the customized correction device after specific training by the qualified healthcare professional.
With the BMPD and DCPP tools it is, therefore, possible to confront and compare the patterns sensed at the beginning of the rehabilitation pathway, as well as to progressively measure (quantitatively and qualitatively) the variations (control steps) applied to the patterns and the effects obtained. Through the use of the BMPD it is therefore possible to validate the effectiveness of these interventions and make them easily repeatable.
For the realization of the system 300, in particular for the realization of the sensors 302, wearable multi-parameter sensors can be conveniently used for sensing movement, distance, orientation and speed of the positions of points of the human body in space, which can be obtained through different technologies. These sensors can be worn by having a direct contact with the skin and/or through specific accessories that simplify their positioning and use for several hours. The requirements of the wearable sensors are miniaturization, compliance for application on the skin, autonomy, low absorption (duration in hours sufficient for the intended use) , connectivity, can communicate with each other and with a wearable control unit, make very accurate measurements, do not require intervention by the patient, are remotely controllable, ensure through appropriate encryption protocols the security and confidentiality of the data produced, are reusable.
Purely by way of example, but in no way limiting nor binding, the sensors 302 may conveniently include movement sensors, accelerometers, magnetometers, surface electromyographs, frequency meters, temperature, oxygenation meters, pressure and/or strain and/or vibration sensors, noise detectors, etc.
Moreover, again purely by way of example, but absolutely not limiting, nor binding, the stimulation devices 303 may conveniently include heat/vibration/cold effectors, etc.
From a software point of view, the processing and control means 304 :
• allow to integrate into the patterns sensed for each specific patient by the BMPD (i.e. by the system 100) the corrective measures defined by the multidisciplinary clinical team;
• acquire the real-time data from the sensors 302 applied to the patient during the period in which he is wearing the correction device 301 to verify the adoption by the patient of the new correct pattern; and,
• if necessary, intervene via the stimulation device (s) 303.
The DCPP software (i.e., the processing and control means 304) is preferably of the embedded type, i.e., resident in the wearable control unit, in order to analyse and return to the BMPD the relevant bio-feedback collected in the ADL period referring to the basic positions (orthostatic, etc.) , in whatever operating condition the patient is in (e.g., absence of external data connectivity) .
In addition, as explained above, the DCPP also has an active function, that is, to signal to the patient in real time the adoption of a "usual pathological pattern" previously identified through the BMPD and therefore known to the patient who adopts it "involuntarily" according to its own automatism (to be corrected) stimulating them to apply the new motor pattern to be taken, in addition to storing and cataloguing information on the measurements they make when they are in the coded positions.
Figures 4A, 4B and 4C show (in particular by means of a flow chart) an example of the use of the system 300 (i.e. DCPP) .
In particular, the steps of use of the system 300 (i.e. of the DCPP) shown in Figures 4A-4C (and progressively numbered from 401 to 423) are absolutely self-explanatory and immediately understandable by any technician in the field, so they will not be described in detail here.
An example of a DCPP is a pelvis setup adjustment device (referred to by the Applicant as the "Pelvis Position Optimizer" - PPO) .
In particular, the PPO is a hardware/sof tware device aimed at correcting usual pathological patterns that involve deviations of the pelvis in the planes of the space. The hardware component consists of sensors and effectors. They are connected to a device (e.g. a smartphone) that sends information from the sensors to a central server which, by processing the data compared with individual standards predetermined by the rehabilitation team together with the individual treatment plan for each subject, provides realtime feedbacks, subsequently taking into account any changes in the patterns and their persistence over time.
3. Final remarks
The following table briefly indicates the market needs and/or use functions required by the market and, for each of these needs/use functions, compares the relative innovative characteristics of the present invention with respect to the traditional solutions and indicates the relative advantages of the present invention.
Figure imgf000023_0001
Figure imgf000024_0001
In order to implement the present invention, both basic components (e.g., sensors, interfaces, etc.) of known type, and specially designed and manufactured for the purpose , can be conveniently used .
Conveniently, the present invention exploits software programs/modules for processing the sensed parameters and for creating a 3D model of the human musculoskeletal system, as well as using speci fic algorithms necessary for the recognition and coding of patterns for the reali zation of multidimensional models of the patterns referred to each patient .
In addition, the aforesaid multidisciplinary team is preferably responsible for the analysis of the motor patterns , the decisions on the strategies to be implemented and the drafting of a timetable with defined obj ectives ( for example , envisaging periodic checks to assess the achievement of intermediate obj ectives and/or to deal with any unforeseen events ) .
From the foregoing description, the multiple innovative features and the innumerable technical advantages of the present invention are immediately apparent to one skilled in the art .
In conclusion, it is important to note that , while the above-described invention refers in particular to very speci fic embodiments , it must not be intended as limited to such embodiments , including within its scope all the variants , modi fications or simpl i fications covered by the enclosed Claims .

Claims

1. Method for sensing position and movement patterns and pathological patterns of a patient, comprising: a) applying to the patient first sensors (101) designed to sense quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient; b) sensing, by means of the first sensors (101) , quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during activities of daily living of the latter; c) generating through the first sensors (101) , based on the sensed quantities, corresponding position and movement data; d) performing, by processing means (102) , a predefined processing of the position and movement data provided by the first sensors (101) determining, based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter; and e) analysing, by the processing means (102) , the position and movement patterns determined to detect one or more pathological patterns of the patient.
2. The method of Claim 1, wherein:
• step d) includes determining, based on the position and movement data provided by the first sensors (101) , multidimensional digital models relating to the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter; and
• step e) includes detecting one or more patient's pathological patterns based on a comparison between the determined multidimensional digital models and predefined reference digital models relating to reference position and movement patterns of the patient.
25
3. The method of Claim 2 , also comprising a preliminary calibration step that is performed before steps a ) -e ) and which includes :
• applying to the patient the first sensors ( 101 ) or second sensors designed to sense quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient ;
• sensing, by means of the first/ second sensors ( 101 ) , reference quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient ;
• generating through the first/ second sensors ( 101 ) , based on the sensed reference quantities , corresponding reference position and movement data ;
• determining, based on the reference position and movement data, the predefined digital reference models to be used in step e ) .
4 . System ( 100 ) for sensing position and movement patterns and pathological patterns of a patient , comprising :
• a plurality of sensors ( 101 ) designed to be worn by, or applied to , a patient during the activities of daily living of the latter and configured to
- sense quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during the activities of daily living of the latter, and
- generate , based on the sensed quantities , corresponding position and movement data; and
• processing means ( 102 ) which are connected to the sensors ( 101 ) to acquire the position and movement data generated by said sensors ( 101 ) and
- programmed to
- perform a predefined processing of the position and movement data acquired determining, based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter and
- analyse the position and movement patterns determined to detect one or more pathological patterns of the patient.
5. The system of Claim 4, wherein the processing means (102) are programmed to:
• perform the predefined processing determining, based on the acquired position and movement data, multidimensional digital models relating to the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter; and
• detect one or more patient's pathological patterns based on a comparison between the determined multidimensional digital models and predefined reference digital models relating to reference position and movement patterns of the patient.
6. The system according to Claim 4 or 5, wherein the processing means (102) are configured to implement one or more predefined artificial intelligence technologies to:
• perform the predefined processing of the position and movement data acquired;
• determine the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter;
• analyse the determined position and movement patterns; and
• detect one or more pathological patterns of the patient .
7. The system of Claim 6, wherein said predefined artificial intelligence technology ( s ) include (s) one or more machine learning techniques.
8. Method for correcting one or more predetermined pathological patterns of a patient, comprising:
A) applying to the patient
- a correction device (301) designed to be worn by, or applied to, said patient during the activities of daily living of the latter to correct one or more predetermined pathological patterns of said patient,
- sensors (302) designed to sense quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient, and
- one or more stimulation devices (303) operable to provide one or more predefined stimulations to the patient ;
B) sensing, by means of the sensors (302) , quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during the activities of daily living of the latter and while he is wearing said correction device (301) ;
C) generating through the sensors (302) , based on the sensed quantities, corresponding position and movement data;
D) performing, by processing and control means (304) , a predefined processing of the position and movement data provided by the sensors (302) determining by the processing and control means (304) , based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter and while he is wearing said correction device (301) ;
E) detecting by the processing and control means (304) , based on the determined position and movement patterns, whether the predetermined pathological pattern (s) persist ( s ) ; and,
F) if the predetermined pathological pattern (s) persist (s) , operating the stimulation device (s) (303) by
28 means of the processing and control means (304) so as to induce the patient to modify the position and movement patterns adopted so as not to adopt said predetermined pathological pattern (s) .
9. The method of Claim 8, wherein:
• step D) includes determining, based on the position and movement data provided by the sensors (302) , multidimensional digital models relating to the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter and while he is wearing said correction device (301) ; and
• step E) includes detecting whether the predetermined pathological pattern (s) persist (s) based on a comparison between the determined multidimensional digital models and one or more predetermined reference digital models relating to said predetermined pathological pattern (s) .
10. The method according to Claim 8 or 9, also comprising a preliminary step which is performed before steps A) -F) and which includes performing the method for sensing position and movement patterns and pathological patterns of a patient as claimed in any one of Claims 1-3 so as to sense said predetermined pathological pattern (s) .
11. The method according to any one of Claims 8-10, comprising testing different stimulation devices (303) to identify the most suitable and/or most efficient stimulation device (s) (303) to stimulate the patient to not adopt the predetermined pathological pattern (s) .
12. System (100) for correcting one or more predetermined pathological patterns of a patient, comprising :
• a correction device (301) designed to be worn by, or applied to, said patient during the activities of daily living of the latter to correct one or more predetermined pathological patterns of said patient;
• a plurality of sensors (302) integrated into the
29 correction device (301) , or designed to be worn by, or applied to, the patient together with the correction device (301) during the activities of daily living of the latter, said sensors (302) being configured to
- sense quantities relating to the position and to the movement of the body, or of one or more predefined parts of the body, of said patient during the activities of daily living of the latter and while he is wearing said correction device (301) and
- generate, based on the sensed quantities, corresponding position and movement data;
• one or more stimulation devices (303) integrated into the correction device (301) , or designed to be worn by, or applied to, the patient together with the correction device (301) during the activities of daily living of the latter, said stimulation device (s) (303) being operable to provide one or more predefined stimulations to the patient; and
• processing and control means (304) which are
- connected to the stimulation device (s) (303) and to the sensors (302) to acquire the position and movement data generated by said sensors (302) and
- programmed to
- perform a predefined processing of the position and movement data acquired determining, based on the predefined processing performed, position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter and while he is wearing said correction device (301) ,
- detect, based on the determined position and movement patterns, whether the predetermined pathological pattern (s) persist (s) and,
- if the predetermined pathological pattern (s) persist (s) , operate the stimulation device (s) (303) so as to induce the patient to modify the
30 position and movement patterns adopted so as not to adopt said predetermined pathological pattern ( s ) .
13. The system of Claim 12, wherein the processing and control means (304) are programmed to:
• perform the predefined processing determining, based on the acquired position and movement data, multidimensional digital models relating to the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter; and while he is wearing said correction device (301) ; and
• detect whether the predetermined pathological pattern (s) persist (s) based on a comparison between the determined multidimensional digital models and one or more predetermined reference digital models relating to said predetermined pathological pattern (s) .
14. The system according to Claim 12 or 13, wherein the processing and control means (304) are configured to implement one or more predefined artificial intelligence technologies to:
• perform the predefined processing of the position and movement data acquired;
• determine the position and movement patterns adopted by the body, or by said predefined part(s) of the body, of the patient during the activities of daily living of the latter and while he is wearing said correction device (301) ;
• analyse the determined position and movement patterns; and
• detect whether the predetermined pathological pattern(s) persist(s) .
15. The system of Claim 14, wherein said predefined artificial intelligence technology ( s ) include (s) one or more machine learning techniques.
31
PCT/IB2022/059327 2021-10-01 2022-09-30 Systems and methods for detecting motor and position patterns of patients WO2023053075A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP21425045 2021-10-01
EP21425045.8 2021-10-01

Publications (1)

Publication Number Publication Date
WO2023053075A1 true WO2023053075A1 (en) 2023-04-06

Family

ID=84364203

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2022/059327 WO2023053075A1 (en) 2021-10-01 2022-09-30 Systems and methods for detecting motor and position patterns of patients

Country Status (1)

Country Link
WO (1) WO2023053075A1 (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2399513A1 (en) * 2010-06-23 2011-12-28 Qatar University System for non-invasive automated monitoring, detection, analysis, characterisation, prediction or prevention of seizures and movement disorder symptoms
US20150164377A1 (en) * 2013-03-13 2015-06-18 Vaidhi Nathan System and method of body motion analytics recognition and alerting
US20170258390A1 (en) * 2016-02-12 2017-09-14 Newton Howard Early Detection Of Neurodegenerative Disease
US9974478B1 (en) * 2014-12-19 2018-05-22 Great Lakes Neurotechnologies Inc. Discreet movement measurement and cueing system for improvement of safety and efficacy of movement

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2399513A1 (en) * 2010-06-23 2011-12-28 Qatar University System for non-invasive automated monitoring, detection, analysis, characterisation, prediction or prevention of seizures and movement disorder symptoms
US20150164377A1 (en) * 2013-03-13 2015-06-18 Vaidhi Nathan System and method of body motion analytics recognition and alerting
US9974478B1 (en) * 2014-12-19 2018-05-22 Great Lakes Neurotechnologies Inc. Discreet movement measurement and cueing system for improvement of safety and efficacy of movement
US20170258390A1 (en) * 2016-02-12 2017-09-14 Newton Howard Early Detection Of Neurodegenerative Disease

Similar Documents

Publication Publication Date Title
Benedetti et al. SIAMOC position paper on gait analysis in clinical practice: General requirements, methods and appropriateness. Results of an Italian consensus conference
Bar-On et al. A clinical measurement to quantify spasticity in children with cerebral palsy by integration of multidimensional signals
Rampp et al. Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients
US8568312B2 (en) Electro diagnostic functional assessment unit (EFA-3)
US5891060A (en) Method for evaluating a human joint
Corradini et al. Early recognition of postural disorders in multiple sclerosis through movement analysis: a modeling study
CN106999065A (en) Use the wearable pain monitor of accelerometry
JP2008501447A (en) Portable medical device for automated electrical coherence analysis in patients
Caviedes et al. Wearable sensor array design for spine posture monitoring during exercise incorporating biofeedback
EP4037565A1 (en) Systems and methods for monitoring the state of a disease using a biomarker, systems and methods for identifying a biomarker of interest for a disease
Tsuji et al. Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices
KR20070122012A (en) Apparatus and method for recognizing and analyzing information of live body
Romanato et al. Quantitative assessment of training effects using EksoGT® exoskeleton in Parkinson's disease patients: A randomized single blind clinical trial
Van Criekinge et al. A full-body motion capture gait dataset of 138 able-bodied adults across the life span and 50 stroke survivors
Moreau et al. Overview on wearable sensors for the management of Parkinson’s disease
Paramento et al. Experimental protocol to investigate cortical, muscular and body representation alterations in adolescents with idiopathic scoliosis
WO2023053075A1 (en) Systems and methods for detecting motor and position patterns of patients
KR20130129637A (en) A biofeedback system and method using emg for rehabilitation therapy system for muscle endurance
Balakrishnan et al. Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors
Pourmoghaddam et al. Identification of changing lower limb neuromuscular activation in Parkinson’s disease during treadmill gait with and without levodopa using a nonlinear analysis index
Henning et al. Validating the walking while talking test to measure motor, cognitive, and dual-task performance in ambulatory individuals with multiple sclerosis
Howell Insole-based gait analysis
Perucca et al. Electromyographic latency of postural evoked responses from the leg muscles during EquiTest Computerised Dynamic Posturography: Reference data on healthy subjects
Cop et al. The Simultaneous Model-Based Estimation of Joint, Muscle, and Tendon Stiffness is Highly Sensitive to the Tendon Force-Strain Relationship
KR20150057429A (en) Apparatus and System Measuring 3-channels Respiration and Method thereof

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22813702

Country of ref document: EP

Kind code of ref document: A1