Mechanism for Adaptive Virtual Reality Feedback1 (2016)

This work presents development and testing of two haptic mechanisms to simulate epidural needle insertion procedure.To configure the force-feedback accuracy, we measured 20 insertions from patients in vivo during a clinical trial. The graphics and forces adapt to the body mass index (BMI) of individual patients.Two haptic mechanisms were constructed: an electromagnetic haptic device (Fig. 1) and a motor-driven haptic device (Fig. 2). The resulting closed-loop system comprises manikin using four sensors and three force-feedback components which can connect to our developed virtual reality epidural simulator 3D computer graphics [1].Our literature review identified that 31 epidural simulators have been implemented for clinical practice over the last 30 years either commercially or for research [2].The purpose of this mechanism is to: (i) connect the manikin device to computer-based virtual reality graphics, (ii) model insertions on various BMIs, (iii) use measured data-driven approach, (iv) track needle orientation and depth using sensors, (v) model accurate loss-of-resistance (LOR) feeling, (vi) saline should escape at loss-of-resistance, (vii) different feeling for each tissue layer, and (viii) mimic cerebrospinal fluid (CSF) leak on dural puncture.Our first haptic mechanism uses electromagnets (Fig. 1). The device implements a force versus depth lookup table for one-directional needle insertion. The principle behind the design uses electromagnets to compress two rubber sheets together, between which runs a shaft connected to the needle. This device generates friction to resist the forward motion.The device has a needle depth sensor resistor with a wheel lined with rubber. The wheel turns as the needle depth is increased. A microcontroller monitors the needle depth to determine the tissue layer. Force and depth data are stored in memory. The microcontroller activates the electromagnet via an MOSFET transistor and diode, protecting from electromagnetic field spikes to increase or decrease the resistance level.Different levels of current are applied to the electromagnet for each tissue layer. The electromagnetic field strength is given by the Ampere's law, as the current is varied, magnet strength varies, and therefore, the friction on the needle can be adjusted programmatically. The method used to vary the current flowing to the electromagnet is the pulse width modulation (PWM). By switching the current on and off at high frequency, the average current can be controlled, by adjusting the time between pulses using the below equation(1)Va=Vi(T/P)where Va is the average voltage, Vi is the input voltage, T is the duration of high-voltage pulse, and P is the period of PWM.Calibration was completed by applying weights up to 15 N to check the current required to generate enough friction for each layer. Springs are fixed between the iron cores and the desk clamp to represent the tissue deformation elasticity. The springs fully compress after 1 cm with 1 N of applied force.A serial port interface was developed to connect the device to a computer providing a visual needle display. The RS232 connection runs at 22 kbits per second which results in data retrieval of 2200 values per second, one value every 0.45 ms. The screen refresh rate is 60 Hz, equivalent to a refresh of every 16.66 ms. The resulting device has a total latency time of 16.66 ms between the sensor and visual display.The second haptic device uses a motor for force feedback (Fig. 2). The motor provides a gripping force on the needle causing friction. The motor shaft is connected to a 250:1 gearbox to increase power, as shown in Fig. 2. The gearbox is connected to a chain which gets pulled as the motor turns. The chain is connected to a wedged sheet of metal. The wedged metal plate causes a compression on the sides of the needle, giving a controllable friction force felt by the user.The mechanism combines four sensors: two actuators for needle inclination and needle depth. There is a strain gauge for measuring the applied force. A pressure transducer measures the applied saline or air pressure. The main force-feedback component is a motor with gearbox which can exert various amounts of friction to model each tissue layer and model various BMIs. A solenoid controls the release of saline to provide an LOR when the needle enters the target epidural space. Also, a pump pushes colored CSF into the syringe which is triggered only when dural puncture occurs.PWM is used to control the speed and torque of the motor. The speed of the motor is set to create the friction which will cause the needle to remain stationary until the applied pressure exceeds the required amount at that needle depth. The components are mounted into a metal plate as shown in Fig. 2. We manufactured various artificial skin materials to cover the front surface based on silicone, gelatine, and glycerin pharmaceutical plasticizer.An ATMega326P microcontroller is installed on a circuit board mounted to the side of the simulator mechanism. The microcontroller has inputs from (i) the motor position sensor, (ii) the needle depth sensor, (iii) the pressure transducer, (iv) the needle angulation sensor, (v) the force from strain gauge, and (vi) the wireless data receiving module. The outputs from the microcontroller connect to (i) the motor, (ii) the solenoid, and (iii) the wireless data transmitter. The motor and solenoid are mounted on a separate circuit board to isolate and protect the microprocessor against power spikes caused by the electromagnetic discharge from the motor coils.The pump is connected into the saline system between the syringe and transducer. This allows pumping of CSF after accidental dural puncture. The disposable pressure transducer is a reliable, accurate, durable clinical component, connected by a three-way tee allowing pressure to be monitored.The solenoid is designed to release saline on LOR by compressing the silicone tube and allowing the liquid to escape. When activated, the solenoid prevents flow through the tube. The solenoid is of high strength to restrict flow in the silicone tube. We used a 12 V solenoid which is compact in size, controlled by a separate 12 V supply to strengthen the power.Our protocol for wireless data transmission uses character strings. Software interprets ASCII values of each character a number from 0 to 31. The numerical system Base 32 was used, and this optimizes the space usage since 322 = 1024. Each of the five sensor readings is represented by 2 bytes in the character string, so ten characters in total are sent wirelessly. Minimizing the data length enables the frequency to be maximized.The software GUI interface enables patient BMI to be adjusted based on an implemented neural network, trained with over 23,000 patient data. The software is able to predict the circumference of waist, thigh, arm calf, and hip from the entered patient parameters over 93% accuracy [1].Motor current over time was measured through the microcontroller. Figure 3 shows initial low current from 20 to 22 s as the motor is not in motion. From 22 to 33 s, the motor is freely turning with no resistance. At 33 s, the motor was not able to move at all which increased current, although current diminished until 37 s when the motor was able to turn freely again. After 40 s, the chain became tighter restricting the motor turning as the wedge began to grip on the needle causing force feedback.We conducted a clinical trial to measure the epidural pressures from 20 obstetric patients. The measurements from the in vivo patients were used to adjust and configure our haptic feedback. Patients of various BMIs were recruited in four subgroups from 18 to 24.9, 25 to 34.9, 35 to 44.9, and >45. Our developed pressure device was used for measuring the insertion pressure in vivo [3].Our clinical measurements demonstrated that there were differences between the insertion pressure in each BMI group, and the average pressure decreased as obesity increased. This may be due to the higher levels of adipose tissue in the ligaments.These haptic needle insertion mechanisms have been connected to our virtual reality graphics interface which can adapt haptic forces to simulate patients of various BMI [1].Our haptic mechanism for needle insertion avoids using commercial haptic devices, such as Geomagic or Novint. Our device can provide a larger range of motion in one degree-of-freedom (DOF), compared to the 6DOF commercial devices.Our clinical trial enabled comparison between our haptic mechanism and measurements from patients in vivo for: (i) simulated transducer pressure versus time, (ii) in vivo transducer pressure versus time (Fig. 4), (iii) strain gauge force versus time, and (iv) simulated transducer pressure versus strain gauge force.The aim of these haptic mechanisms is to form the basis of a hybrid virtual–physical simulator, providing benefits of a tactile physical manikin simulator plus the 3D visualization, data-driven accuracy of virtual reality simulators.