Systems, apparatuses and methods for controlling prosthetic devices by gestures and other modalities

{
  "publication_number": "US10852835B2",
  "country": "US",
  "kind": "B2",
  "title": "Systems, apparatuses and methods for controlling prosthetic devices by gestures and other modalities",
  "abstract": "Systems and methods for manual gesture recognition to control prosthetic devices. Low encumbrance systems utilizing glove-based recognition to control prosthetic devices. Prosthetic control systems and methods are also provided utilizing elements for application on the user's fingernails.",
  "claims": [
    "1. A system, comprising: a signal element configured to generate a signal, wherein the signal element comprises an LED; a fingernail mount configured to secure the signal element on a fingernail of a finger of a user such that the signal element is facing the fingernail; and a detection element configured to detect the signal generated by the signal element, wherein the detection element comprises a light detector; wherein the detection element comprises a circuit configured to determine that the user has performed a gesture based on detecting light from the LED passing through both the fingernail and the finger of the user in response to movement of the LED; and wherein the circuit of the detection element is configured to determine, based on detecting the signal generated by the signal element, that the user has performed a pinch gesture using two or more fingers of the user.",
    "2. The system according to claim 1, wherein the detection element is further configured to detect a characteristic of the signal, the characteristic of the signal indicative of a characteristic of the gesture.",
    "3. The system according to claim 2, wherein the characteristic of the signal comprises at least one of: a frequency; a color; an RFID tag ID; a signal intensity, strength, or amplitude, or change therein; a timing thereof; a resonant frequency of a circuit transmitting or generating the signal; and a frequency or pulse pattern.",
    "4. The system according to claim 2, wherein the characteristic of the gesture comprises at least one of: a particular finger or fingers used; a particular position of one or more fingers; a particular grasp pattern or pose of one or more fingers; a particular movement performed by one or more fingers; and a state of contact or non-contact of one or more fingers with another one or more fingers or with another part of the hand.",
    "5. The system according to claim 1, further comprising a controller configured to control a prosthetic device based on the signal detected by the detection element.",
    "6. The system according to claim 5, wherein the control of the prosthetic device causes the prosthetic device to perform an action or a movement corresponding to the gesture."
  ],
  "description_excerpt": "This disclosure relates generally to systems and methods in the field of wearable electronics and human control interfaces. More specifically, the disclosure relates to techniques for recognizing signals to control powered prosthetic devices providing extended freedom of motion and optional modalities of operation.\n\nThe state of the art for commercial robotic prosthetic systems is to use a pair of electromyography (EMG), also referred to as surface electromyography (SEMG), sensors on the residual limb. These sensors detect the electrical activity of the muscles in the user's remaining limb during muscle activation. For prosthetic hand devices, grasp patterns are typically selected by scrolling through “menus” by co-contracting different muscles (e.g., biceps and triceps) and putting the prosthetic device in different operating modes. Some systems also allow grasp selection via apps running on a smart phone.\n\nConventional prosthetic systems allow users to regain some lost functionality, but in a limited way. For example, prosthetic hand devices typically allow the user limited “open” or “close” functionality. While current powered prosthetic devices boast multiple degrees of freedom and dexterity levels that allow a user to perform a number of operations and movements, interaction with these devices is still limited, and limiting, outside of the clinical setting. EMG data acquisition is highly variable and subject to noise due to linear distances along the surface of the skin above the sensed muscle. Perspiration and user fatigue can also cause degraded device performance.",
  "cpc": [
    "G06F 3/017",
    "A61F 2/583",
    "A61F 2/68",
    "A61F 2/72",
    "A61F 2002/6881",
    "A61F 2002/704",
    "A61F 2002/705",
    "A61F 2002/707",
    "G06F 1/163",
    "G06F 3/014",
    "G06F 3/015"
  ],
  "ipc": [
    "A61F 2/72",
    "G06F 3/01",
    "A61F 2/70",
    "G06F 1/16"
  ],
  "assignees": [
    "University of Texas System"
  ],
  "inventors": [
    "Oguz Yetkin",
    "Joseph D. Sanford",
    "Dan O. Popa",
    "Lena C. Wallace",
    "Fahad Mirza",
    "Roopak Karulkar",
    "Sumit Kumar Das",
    "Joshua R. Baptist",
    "J. Paul Carpenter"
  ],
  "filing_date": "2017-04-16",
  "publication_date": "2020-12-01",
  "grant_date": "2020-12-01",
  "priority_date": "2016-04-15",
  "application_number": "US-201715488500-A",
  "family_id": "60039225",
  "cited_by_count": 3,
  "citations": [
    "US6344062B1",
    "US20100231505A1",
    "US20080215162A1",
    "US20170031453A1",
    "US20160084650A1",
    "US9939899B2"
  ]
}