Multi-user smartglove for virtual environment-based rehabilitation

Abstract

A low-cost, virtual environment, rehabilitation system and a glove input device for patients suffering from stroke or other neurological impairments for independent, in-home use, to improve upper extremity motor function, including hand and finger control. The system includes a low-cost input device for tracking arm, hand, and finger movement; an open source gaming engine; and a processing device. The system is controllable to provide four types of multiple patient/user interactions: competition, cooperation, counter-operative, and mixed.

1 . A multiple-user virtual environment system for rehabilitation exercise of mammalian trunk, extremities, and digits, the system comprising:
 a communication network; and   a plurality of individual virtual environments, each of the individual virtual environments including:
 at least one input device that is structured and arranged to generate at least one of movement, orientation, velocity, and position data corresponding to discrete movement of a portion of the mammalian trunk or of one or more mammalian extremities or digits, 
 a processing device that is adapted to receive the at least one movement, orientation, velocity and position data from the input device; to store said movement, orientation, velocity, and position data; and to generate image data therefrom for display on a display device, and 
 a virtual environment interface that is adapted to enable virtual environment communication and virtual environment data transfer between the processing device and the network. 
   
     
     
         2 . The system as recited in  claim 1  further comprising an interface and processing device that enable a third party to observe and to record data from the processing device. 
     
     
         3 . The system as recited in  claim 2 , wherein the third-party processing device is structured and arranged to pre-establish or adapt at least one rehabilitation exercise for each of the plurality of virtual environments or to modify said exercise or virtual environment. 
     
     
         4 . The system as recited in  claim 4 , wherein the third-party processing device is structured and arranged to pre-establish a type of multi-user interaction for each of the at least one rehabilitation exercise and for each of the plurality of virtual environments. 
     
     
         5 . The system as recited in  claim 4 , wherein the type of multi-user interaction is selected from the group consisting of a competitive interaction, a counter-operative interaction, a cooperative interaction, and a mixed interaction. 
     
     
         6 . The system as recited in  claim 4 , wherein the third-party processing device is structured and arranged to adjust a degree of difficulty for each of the at least one rehabilitation exercises. 
     
     
         7 . The system as recited in  claim 1 , wherein the virtual environment interface includes at least one of:
 game engine hardware having a programming code and a plurality of rules,   game engine software having a programming code and a plurality of rules,   a scripting programming code that is capable of overwriting low-level game engine programming code,   three-dimensional model software that is adapted to populate the engine programming code and to adhere to the plurality of rules, and   three-dimensional graphic software that is adapted to populate the engine programming code and to adhere to the plurality of rules.   
     
     
         8 . The system as recited in  claim 1 , wherein the network is selected from the group consisting of a local area network, a wide area network, the World Wide Web, and the Internet. 
     
     
         9 . The system as recited in  claim 1 , wherein the network is adapted to generate a virtual reality environment using the virtual environment data. 
     
     
         10 . The system as recited in  claim 1 , wherein the input device is adapted to monitor a position or an attitude of an extremity or of a digit in space. 
     
     
         11 . The system as recited in  claim 1 , wherein the discrete movement is selected from the group consisting of movement in an x-direction, movement in a y-direction, movement in a z-direction, pitch, roll, and yaw, wherein each of the x-direction, the y-direction, and the z-direction is mutually perpendicular. 
     
     
         12 . The system as recited in  claim 1  further comprising a base unit that, in combination with the at least one input device, is structured and arranged to provide a dead reckoning starting and a dead reckoning ending point-of-reference, to enable the processing device to determine at least one of attitude and velocity of said at least one input device. 
     
     
         13 . The system as recited in  claim 12 , wherein the base unit is selected from the group comprising a banana grip base, a globe base, a pyramidal base or a tear-drop base. 
     
     
         14 . The system as recited in  claim 13 , wherein the globe base includes imprinted grooves that define the dead reckoning starting and the dead reckoning ending point-of-reference. 
     
     
         15 . The system as recited in  claim 14 , wherein the base unit includes adjustable arm splints for neutral wrist position and forearm support. 
     
     
         16 . The system as recited in  claim 1 , wherein the at least one input device comprises a pair of gloves. 
     
     
         17 . The system as recited in  claim 1 , wherein the processing device is adapted to map real world movement directly into similar or abstractly into different virtual world movement. 
     
     
         18 . The system as recited in  claim 1  further comprising a teacher model capability to highlight shortcomings and errors of the user and to demonstrate how to correct said shortcomings and errors. 
     
     
         19 . An input device for use with a multiple-user virtual environment system for rehabilitation exercise of a human hand and digits, the input device being structured and arranged to generate signals corresponding to at least one of a discrete movement and an attitude of said hand and said digits, the device comprising:
 a glove that can be readily donned and doffed on either hand by a user, the glove having finger portions for at least a thumb, an index finger, a middle finger, and a ring finger;   a first plurality of sensors, each sensor being structured and arranged to provide data on movement and range of movement of at least one of the index finger, the middle finger, and the ring finger, each of the first plurality of sensors being disposed within the finger portions of said index finger, said middle finger, and said ring finger;   a second plurality of sensors that is structured and arranged to provide data on movement of the thumb; and   a positioning and tracking system that is structured and arranged to generate position coordinates in three rotational axes and three translational axes to determine at least one of the attitude and a velocity of said hand.   
     
     
         20 . The input device as recited in  claim 19 , wherein the first and the second pluralities of sensors are selected from the group comprising electronic bend sensors, resistive bend sensors, capacitive bend sensors, optical fiber sensors, mechanical measurement bend sensors, angle measurement sensors, Hall effect sensors or electromechanical sensors. 
     
     
         21 . The input device as recited in  claim 19 , wherein the positioning and tracking system is selected from the group comprising an inertial measurement unit (IMU), a radio frequency (RF) positioning and tracking system, an infrared positioning and tracking system, three-dimensional cameras or a magnetic tracking system. 
     
     
         22 . The input device as recited in  claim 21 , wherein the positioning and tracking system is an inertial measurement unit (IMU) that employs dead reckoning to determine the attitude of the hand and the velocity of the hand. 
     
     
         23 . The input device as recited in  claim 22 , the input device further including a Hall effect sensor for zeroing the IMU. 
     
     
         24 . The input device as recited in  claim 19 , wherein the device has a total weight that does not exceed sixteen ounces. 
     
     
         25 . The input device as recited in  claim 24 , wherein a dorsal weight on the input device does not exceed eight ounces. 
     
     
         26 . The input device as recited in  claim 19 , wherein the input device is structured and arranged to measure at least one of the following accurately:
 finger flexion/extension measured to at least 90°;   wrist flexion/extension or dorsal action at ±90°;   wrist-radial deviation up to 40°;   wrist-ulnar deviation up to 50°; and   forearm supination/pronation up to 180°.   
     
     
         27 . The input device as recited in  claim 19  further comprising a feedback system that is selected from the group comprising an audible speaker to provide auditory clues, at least one light-emitting device to provide a visual signal, and a haptic device to provide a vibratory signal. 
     
     
         28 . The input device as recited in  claim 19  further comprising a touch sensor that is adapted to provide and record pinch data, the touch sensor being disposed in a tip portion of the glove thumb and being activated by contact with any of the index finger, the middle finger, the ring finger or a pinky finger. 
     
     
         29 . The input device as recited in  claim 19  further comprising a communication means for providing hand and finger movement data and attitude data to a processing unit. 
     
     
         30 . The input device as recited in  claim 19  further comprising a pulley portion to measure radial and ulnar deviations, the pulley portion being disposed above a user's elbow and being releasably attached to a medial side of the glove. 
     
     
         31 . A method of providing a virtual environment system for rehabilitation exercise to a plurality of users over a communication network, the method comprising:
 providing an individual virtual environments to each of the plurality of users, each of the individual virtual environments including an input device, a processing device, and a virtual environment interface;   generating at least one of movement, orientation, velocity, and position data signals corresponding to discrete movement of one or more mammalian trunk, extremities or digits disposed in the input device;   receiving the data signals from the input device;   generating image data for display on a display device and other data from said input data; and   enabling virtual environment communication and virtual environment data transfer between the processing device and the network.   
     
     
         32 . The method as recited in  claim 31  further comprising enabling a third party to observe and to record image and other data from the processing device. 
     
     
         33 . The method as recited in  claim 31  further comprising pre-establishing at least one rehabilitation exercise for each of the plurality of virtual environments. 
     
     
         34 . The method as recited in  claim 31  further comprising pre-establishing a type of multi-user interaction for each of the at least one rehabilitation exercise and for each of the plurality of virtual environments. 
     
     
         35 . The method as recited in  claim 34 , wherein the type of multi-user interaction is selected from the group consisting of a competitive interaction, a counter-operative interaction, a cooperative interaction, and a mixed interaction. 
     
     
         36 . The method as recited in  claim 31 , wherein the discrete movement is selected from the group consisting of movement in an x-direction, movement in a y-direction, movement in a z-direction, pitch, roll, and yaw, wherein each of the x-direction, the y-direction, and the z-direction is mutually perpendicular. 
     
     
         37 . The method as recited in  claim 31  further comprising generating a virtual reality environment using the virtual environment data. 
     
     
         38 . The method as recited in  claim 31  further comprising monitoring a position of an extremity or of a digit in space. 
     
     
         39 . The method as recited in  claim 31  further comprising:
 scoring user performance using said input data; and 
 displaying scoring results after each exercise, daily, weekly, after each session, after each phase of an exercise and/or immediately. 
 
     
     
         40 . The method as recited in  claim 31  further comprising amplifying the data signals corresponding to the at least one of movement, orientation, velocity, and position before displaying image data generated therefrom. 
     
     
         41 . The method as recited in  claim 34  further comprising adjusting a degree of difficulty of said at least one rehabilitation exercise.