A flexible fiber optic sensor for use in data gloves, its fabrication method, testing method, and application.

Abstract

This invention provides a flexible fiber optic sensor for use in data gloves, its fabrication method, testing method, and application. The invention includes a flexible optical fiber, a light source, a power supply, a miniature camera, and an external package encapsulating these components. The power supply is connected to the light source. The miniature camera is used to collect changes in the grayscale value of the flexible optical fiber cross-section. A control fiber is provided between the light source and the miniature camera to compensate for changes in light intensity caused by a decrease in power during use. The flexible optical fiber is U-shaped and its length exceeds the length of a finger. It is folded by a shaft and embedded into a latex tube, which is then indirectly bonded to the data glove. This invention uses a simple, stable, economical, and controllable method to fabricate a flexible optical fiber with adjustable and stretchable properties. The flexible optical fiber used for gesture sensing and monitoring exhibits good flexibility, stability, and accuracy.

Description

Technical Field

[0001] This invention relates to the field of fiber optic sensing technology, and in particular to a flexible fiber optic sensor for use in data gloves, its preparation method, testing method, and application. Background Technology

[0002] In recent years, with the development of virtual reality interaction technology, researchers have become increasingly enthusiastic about flexible, stretchable, and wearable sensor devices capable of tracking complex human movements. The human hand, with over 20 degrees of freedom, possesses flexible functions in communication and manipulation, can transmit vast amounts of information, and is one of the most important organs for human-computer interaction. Data gloves have become one of the main devices in human-computer interaction technology, widely used in education, healthcare, gaming, film, and other fields.

[0003] Currently, data glove devices are mainly based on point tracking and recognition technology, computer vision technology, FBG sensor technology, and inertial sensors. However, each of these technologies has its own drawbacks. In point tracking and recognition technology, markers can be electromagnetic, acoustic, or optical. However, electromagnetic and acoustic markers have limitations during hand movements, such as susceptibility to electromagnetic interference and low resolution. Optical markers are easily obscured. Data gloves based on computer vision technology have specific requirements for applications, system operating environments, and ambient light conditions. FBG sensors have high sensitivity and accuracy, but their complex measurement systems limit their application in data gloves. Data gloves based on inertial sensors offer good real-time gesture measurement performance. However, inertial sensors suffer from cumulative measurement errors and are not suitable for prolonged operation. Furthermore, to fully capture hand movements and senses, data gloves based on these technologies require embedding multiple sensors on each finger. This sensor fusion increases the complexity of the data glove system and reduces its portability and practicality.

[0004] Optical sensors offer advantages such as resistance to electromagnetic interference and high reliability, but one issue warrants attention: the light sources used in optical sensors are frequently affected by factors such as current fluctuations. This is especially true in mobile devices equipped with independent batteries, where battery aging can reduce the current intensity flowing to the light source, causing changes in light intensity and introducing errors into the measurement system. Therefore, implementing effective and easily implementable measures to reduce system errors caused by light source instability is crucial for the further development of flexible fiber optic sensors. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a flexible fiber optic sensor for use in data gloves, its fabrication method, testing method, and applications. The technical means employed in this invention are as follows:

[0006] A flexible fiber optic sensor for use in data gloves includes a flexible fiber optic cable, a light source, a power supply, a miniature camera, and an external package encapsulating the components. The power supply is connected to the light source. The miniature camera is used to collect changes in the grayscale value of the flexible fiber optic cable cross-section. A reference fiber optic cable is provided between the light source and the miniature camera to compensate for changes in light intensity caused by a decrease in power during use. The flexible fiber optic cable is U-shaped and its length exceeds the length of a finger. It is folded in half by a shaft and embedded in a latex tube, which is then indirectly bonded to the data glove.

[0007] Furthermore, the flexible optical fiber is composed of a double-layer coaxial cylindrical rubber structure, with the core material being a two-component RTV silicone rubber and the cladding material being a two-component addition-type liquid silicone rubber.

[0008] Furthermore, the flexible optical fiber is mounted on the data glove with a bending radius of 5±1mm.

[0009] This invention also discloses a method for manufacturing the above-mentioned flexible optical fiber sensor, comprising the following steps:

[0010] Step 1: Prepare the liquid materials for the core layer and the cladding layer, defoam the liquid materials, and inject the defoamed liquids into syringes A and B respectively;

[0011] Step 2: Spray a layer of oily release agent onto the mold. After the release agent dries, place the heat shrink tubing into the hollow tube and fix the heat shrink tubing in the center of the hollow tube with a positioning plug.

[0012] Step 3: Use syringe A to inject the defoaming cladding solution into the interlayer between the acrylic tube and the heat shrink tube. After standing for a period of time, place it in a drying oven to cure. Then, raise the temperature and adjust the diameter of the heat shrink tube to the preset value before pulling it out. The cladding solution forms a stretchable transparent hollow tube as the cladding of the flexible optical fiber.

[0013] Step 4: Inject the defoamed core solution into the cladding using syringe B, let it stand for a period of time, then place it in a drying oven to cure, and pull the flexible optical fiber out of the hollow tube.

[0014] The present invention also discloses a test method for the above-mentioned flexible optical fiber sensor, including bending test, tensile test and indentation test.

[0015] Furthermore, the specific testing method includes the following steps:

[0016] The bending radius-normalized light intensity relationship diagram at the corresponding wavelength is determined based on the selected light source.

[0017] By sequentially increasing the tensile strain, the strain-normalized light intensity relationship of the optical fiber was measured.

[0018] Measure the length-normalized light intensity relationship of optical fibers of different lengths;

[0019] Different pressures were applied sequentially to the side of the optical fiber to obtain pressure-normalized light intensity curves.

[0020] The optical fiber was repeatedly bent from a straight state to a bent state, and the normalized spectrum of the optical fiber was measured after a preset number of times.

[0021] The tensile strain of the optical fiber was repeatedly adjusted, and the normalized spectrum of the optical fiber was measured after a preset number of times.

[0022] Under the premise of repeatedly adjusting the tensile strain of the optical fiber, the sensing performance of a straight optical fiber of the same length and a folded optical fiber were compared.

[0023] Under the premise of repeatedly adjusting the tensile strain of the optical fiber, the average normalized light intensity of the optical fiber was measured a preset number of times at different temperatures.

[0024] The present invention also discloses a data glove that uses a flexible fiber optic sensor that has undergone the above-mentioned tests.

[0025] Furthermore, the data processing of the control system of this data glove includes the following steps: preprocessing-self-calibration, data processing, robust fine-tuning, self-compensation processing, and intelligent prediction.

[0026] The preprocessing-self-calibration specifically includes: adjusting the zero point position and amplitude of the sensor. During the adjustment process, the user performs a series of specific gestures in advance to obtain values ​​that match the user's hand shape. After preprocessing, the maximum and minimum bending gray values ​​of each finger at the extreme position and the gray value in the half-grip state are collected. The data glove adapts to different hand shapes and bending habits.

[0027] The data processing specifically includes: transmitting the mapping relationship between grayscale values ​​and specific gestures to the system for automatic calibration; linking the pre-processed mapping relationship with the servo motor of the manipulator to construct a new mapping relationship; and transferring the five real-time grayscale values ​​to the robotic hand through the mapping relationship in the system to achieve real-time gesture tracking.

[0028] Robust fine-tuning specifically includes: the system statistically analyzes the extreme values ​​encountered based on the abnormal situations, and performs robust fine-tuning after exceeding a preset number of times;

[0029] The self-compensation processing specifically includes: when the brightness of the light source decreases during sensor application due to power supply issues, the cross-sectional brightness of the five reference optical fibers will decrease proportionally along with the brightness of the light source. This proportional decrease is eliminated by correcting the grayscale, and a corrected grayscale value close to the theoretical value is obtained.

[0030] The intelligent prediction process involves: acquiring data on the impact of a moving finger on adjacent fingers, constructing a prediction library related to the movement, and obtaining a compensation function relationship based on the error patterns in the prediction library.

[0031] Furthermore, the specific formula for the self-compensation process is as follows:

[0032]

[0033] Where I0 represents the initial luminance of the plastic reference fiber cross-section, approximately equal to the initial luminance of the light source; I r The real-time luminance of the plastic reference fiber cross-section is approximately equal to the real-time luminance of the light source; when i = 1, 2, 3, 4, 5, L i and I i These represent the initial and real-time luminous intensity of the fiber cross-section corresponding to each finger, respectively.

[0034] This invention proposes a self-compensating flexible fiber optic sensor and a low-cost flexible data glove based on this sensor, featuring a simple sensing mechanism, self-calibration function, and ease of operation. A simple, stable, economical, and controllable method was used to prepare stretchable flexible silicone rubber fibers. The optical loss after 100 repeated bending cycles with a 5mm bending radius was only 2%. The U-shaped fiber exhibited good repeatability, stability, and mechanical durability within the 0–100% tensile strain range. Within a temperature range of 10℃–50℃, when the U-shaped fiber was repeatedly stretched 100 times within the 0–50% strain range, the fiber loss was less than 15%. The fiber showed strong resistance to lateral pressure. Even under a 50N pressure, the fiber still transmitted approximately 30% of the light. Compared to a straight fiber, the U-shaped fiber showed a maximum increase in deformation response sensitivity of approximately 7 times. An additional communication-grade plastic fiber (attenuation less than 180dB / km) was incorporated into the sensor as a reference signal. This reference fiber effectively improved the stability and accuracy of the sensor system. The camera- and algorithm-based detection section enabled compact and efficient real-time information acquisition and processing. The sensor is easy to install, allowing the data glove size to be adjusted according to the type of textile glove. Furthermore, the self-calibration function improves the accuracy of data acquisition, and the data glove adapts to different hand sizes and bending habits. In gesture capture tests, the data glove accurately identified and captured each gesture. The robotic arm can react quickly and perform the same action. The data glove has a simple and stable structure, is low-cost, and easy to manufacture and customize. It can monitor finger joint movements in real time, accurately, and effectively. It has potential application value in fields such as motion monitoring, telemedicine, and human-computer interaction. With the continuous development of virtual reality interaction technology, the application areas of this data glove will become even more extensive. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic diagram of the flexible fiber optic sensor structure of the present invention.

[0037] Figure 2 This is a schematic diagram of the data glove of the present invention, including a schematic diagram of the external structure and a schematic diagram of the fiber optic arrangement.

[0038] Figure 3 This is a schematic diagram of the preparation process of the present invention.

[0039] Figure 4 The test diagrams obtained during the mechanical and optical performance testing process of this invention are shown in the figure. (a) is a graph showing the relationship between the bending radius and the normalized light intensity at a wavelength of 650 nm; (b) is the mechanical performance of the optical fiber in a bent state; A is the extinction point of the strain-normalized light intensity curve of the optical fiber; (c) is the measurement of the normalized light intensity to quantify the propagation loss by shortening the optical fiber from 20 cm to 10 cm; and (d) is a graph showing the relationship between the pressure and the normalized light intensity at a wavelength of 650 nm.

[0040] Figure 5 The following are test images obtained from the repeated bending and stretching test process of this invention. In the figure, (a) is the normalized spectrum of the optical fiber in the wavelength range of 530-690nm after 100 bending cycles; (b) is the normalized spectrum of the optical fiber in the wavelength range of 530-690nm after 100 stretching cycles; (c) is the relationship between the light intensity and strain of the optical fiber in a straight state with a length of 10cm and the optical fiber in a folded state with a length of 10cm; and (d) is the average normalized light intensity of the optical fiber at 650nm after 50 cycles of stretching at 5 different temperatures.

[0041] Figure 6 This is a schematic diagram of the data collection and processing process of the present invention.

[0042] Figure 7 This is a diagram illustrating the changes in gestures and grayscale values. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] This invention discloses a flexible fiber optic sensor for use in data gloves. The flexible fiber optic sensor quantifies fiber deformation by measuring light loss throughout the finger during propagation. The use of data gloves involves many uncertainties, such as the influence of the hand's cartilage on the sensor. Flexible fiber optics are inherently force-sensitive materials; even minute disturbances can cause changes in the output value. Therefore, the installation of flexible fiber optics needs to conform as closely as possible to the user's hand shape. To this end, such as... Figure 1 , Figure 2 As shown, this invention specifically includes a flexible optical fiber, a light source, a power supply, a miniature camera, and an external package encapsulating the above components. The power supply is connected to the light source. The miniature camera is used to collect changes in the grayscale value of the flexible optical fiber cross-section. A reference optical fiber is provided between the light source and the miniature camera to compensate for changes in light intensity caused by a decrease in power during use. The flexible optical fiber is U-shaped and its length exceeds the length of a finger, specifically approximately twice the length of a finger. It is folded in half using a 5mm axle and embedded in a black latex tube. The latex tube is then indirectly bonded to the data glove. This design increases the deformation area of ​​the flexible optical fiber, disperses pressure at the knuckles, increases the lifespan of the flexible optical fiber, and prevents relative displacement during each use while still ensuring a comfortable fit for the user's fingers. Specifically, to enhance the bonding strength between the latex tube and the glove, a surface treatment agent can be used before bonding, followed by bonding with a soft silicone adhesive. This ensures a soft and comfortable feel for the glove, increases the accuracy of the sensor in collecting finger movements, and prevents unnecessary interference. During data acquisition, the U-shaped design can also amplify minute changes in finger quantification, increasing the sensitivity of the data glove.

[0045] In this embodiment, to ensure the portability of the data glove, a 5mm ultra-bright LED with a wire is selected as the light source, powered by two button batteries. An 8-megapixel miniature camera is used to collect changes in the grayscale value of the fiber optic cross-section. An additional 5±1cm communication-grade plastic optical fiber (attenuation less than 180dB / km) is installed between the light source and the camera to compensate for changes in light intensity caused by the gradual decrease in battery power during use. To prevent interference from external light and the LED light source, the entire acquisition module is encapsulated with a black acrylic plate, and epoxy resin putty is used to internally fix the camera and flexible optical fiber, ensuring stable data acquisition during use. This data glove, based on fiber optic sensing, can shield against electromagnetic interference, has a simple structure, can be used on gloves of different sizes, and is lightweight and stable. Furthermore, this low-cost data glove, based on a self-compensating flexible fiber optic sensor, has a simple sensing mechanism and self-calibration function, and can be used for gesture capture.

[0046] The flexible optical fiber is composed of a double-layer coaxial cylindrical rubber structure. The core material is a two-component RTV silicone rubber, and the cladding material is a two-component addition-type liquid silicone rubber.

[0047] The flexible optical fiber is mounted on the data glove with a bending radius of 5 mm.

[0048] Deformations such as bending and stretching alter the light propagation path in optical fibers, making total internal reflection impossible. The light propagation mode changes from transmission mode to radiation mode, causing some light to scatter outwards through the cladding, resulting in light loss. Natural hand movements are regular and subject to inherent constraints: the three phalanges of the fingers move within the same plane, and the muscles and soft tissues of the hand ensure that the movement of one phalanx necessitates the coordinated movement of adjacent phalanges. In this context, the degree of finger bending can be determined by measuring the total loss of the entire finger, which is the basis for the ability of data gloves to capture gestures.

[0049] To meet these standards, the flexible optical fiber consists of a double-layer coaxial cylindrical rubber structure. The core and cladding are made of high-refractive-index silicone rubber (RI = 1.413) and low-refractive-index silicone rubber (RI = 1.411), respectively. The cross-sectional diameters of the core and the entire fiber are 1.5 ± 0.1 mm and 2.9 ± 0.1 mm, respectively, and the fiber length is 40 ± 3 cm. This size of fiber ensures both quantization of the finger and excellent reusability and toughness.

[0050] like Figure 3 As shown, the present invention also discloses a method for manufacturing the above-mentioned flexible optical fiber sensor. This method can not only reduce interference from external debris during the manufacturing process, but also simplify the manufacturing process. Specifically, it includes the following steps:

[0051] Step 1: Prepare the liquid materials for the core and cladding layers. Degas the liquid materials, and inject the degassed liquid into syringes A and B respectively. Specifically, the core material is a two-component RTV silicone rubber, and the cladding layer uses a two-component addition-type liquid silicone rubber. The solvent and crosslinking agent are mixed at a weight ratio of 10:1. After thorough stirring, the liquid is placed in a vacuum pressure pump for degassing. Inject the degassed liquid into syringes A and B respectively, and let it stand for 5–30 minutes until no more bubbles are generated in the liquid (bubbles will affect the refractive index and toughness of the fiber).

[0052] Step 2: To make demolding easier, apply a layer of oily release agent to the mold. After the release agent dries, place the heat shrink tubing inside the hollow tube and fix the heat shrink tubing in the center of the hollow tube with a positioning plug. In this embodiment, the inner diameter of the heat shrink tubing is 1.5±0.1mm, and the inner diameter of the hollow tube is 2.9±0.1mm. It is an acrylic hollow tube.

[0053] Step 3: Inject the defoaming cladding solution into the interlayer between the acrylic tube and the heat shrink tubing using syringe A. After standing for a period of time, place it in a drying oven for curing. Then, raise the temperature and adjust the diameter of the heat shrink tubing to the preset value before pulling it out. The cladding solution forms a stretchable transparent hollow tube as the cladding of the flexible optical fiber. In this embodiment, it is placed for 5 to 30 minutes until no bubbles appear. The initial curing temperature in the drying oven is 50±5℃. The drying oven is heated to 90±5℃ until the heat shrink tubing shrinks to 1 / 3 of its own diameter before pulling it out. After cooling to room temperature, the transparent hollow tube is formed.

[0054] Step 4: Inject the defoaming core layer solution into the cladding using syringe B. After standing for a period of time, place it in a drying oven for curing. Then pull the flexible optical fiber out of the hollow tube. Tiny air bubbles are very likely to appear during this process. Therefore, it can be placed in a natural environment until the bubbles are expelled. After confirming that there are no air bubbles in the fiber, place it in a drying oven and wait for curing to complete at 90±5℃. Then cool it to room temperature. The completed flexible optical fiber can be stretched and bent arbitrarily, exhibiting a certain degree of toughness and recoverability.

[0055] To quantitatively evaluate the mechanical and optical properties of flexible optical fibers in response to deformation, this invention also discloses testing methods for the aforementioned flexible optical fiber sensors, including bending tests, tensile tests, and indentation tests.

[0056] The specific testing method includes the following steps:

[0057] The optical fiber is mounted on the data glove in a U-shaped bend. Choosing a suitable bend radius to avoid extinction and meet sensor requirements is crucial. Therefore, in the bend test, normalized light intensity curves were measured at different bend radii. Since the deformation sensor uses a 5mm ultra-bright LED with a red lead as the light source, the bend radius-normalized light intensity relationship at a wavelength of 650nm was selected. Figure 4 a) It can be seen that the light intensity passing through the optical fiber decreases as the bending radius decreases. However, as the bending radius of the optical fiber decreases from infinity to 2.5 mm, at least 30% of the light can still pass through the optical fiber, which is a prerequisite for the use of optical fiber for sensing.

[0058] Based on the results of the bending test and the design of the data glove, a bending radius of 5 mm was chosen to mount the optical fiber on the data glove. To investigate the mechanical properties of the optical fiber under bending conditions, the strain-normalized intensity curve of the folded fiber at a wavelength of 650 nm was also measured. Figure 4 As shown in Figure b, the optical fiber maintains its mechanical integrity under 100% tensile strain. As the strain increases from 100% to 110%, the strain-normalized intensity curve shows an extinction point A. Point A indicates that extinction occurs when the fiber elongation exceeds 100%, but no breakage occurs. To characterize the optical performance of the fiber, the fiber is shortened sequentially from 20 cm to 10 cm, and the normalized intensity is measured to quantify its propagation loss. Figure 4 As shown in Figure c, the normalized light intensity decreases with increasing fiber length. This is because the increased fiber length leads to a longer path for light through the attenuating medium. In the indentation test, pressures ranging from 10 to 100 N were applied sequentially to the side of the fiber at 10 N intervals. The pressure-normalized light intensity relationship was measured at a wavelength of 650 nm, as shown in Figure c. Figure 4 As shown in diagram d, it can be seen that the light intensity through the optical fiber decreases with increasing pressure. The transmission loss caused by lateral pressure on the optical fiber is due to the light propagation path failing to meet the critical angle requirement for total internal reflection. Figure 4 As shown in diagram d, the flexible optical fiber can still transmit about 30% of the light even when subjected to a pressure of 50N. This indicates that the optical fiber used for sensing has a strong resistance to lateral pressure. Moreover, the deformation sensor mounted on the data glove will almost never be subjected to pressure exceeding 30N in practical applications.

[0059] After evaluating the mechanical and optical properties of the optical fiber, the optical response of the fiber to disturbances caused by repeated bending and stretching was also tested. For the bending response evaluation, the fiber was bent from a straight state to a bending radius of 5 mm, and then returned to a straight state; this constituted one cycle. One hundred cycles were performed, and the normalized spectrum of the fiber in the wavelength range of 530–690 nm was measured after each cycle. Figure 5 As shown in Figure a, it can be seen that during 100 bending cycles, the normalized light intensity distribution in the optical fiber ranges from 0.98 to 1.00, with a normalized light intensity loss of only 2%. In the stretching cycle, a period is defined as the tensile strain increasing from 0% to 50% and then returning to 0%. An optical fiber with a bending radius of 5 mm is repeatedly stretched over 100 cycles, and the normalized spectrum of the fiber in the wavelength range of 530–690 nm is measured after each cycle. Figure 5 As shown in b, during this cycle, it can be seen that after the first cycle, the normalized light intensity in the fiber decreases from 1.00 to approximately 0.98. However, in the next 99 cycles, after each cycle, the normalized light intensity in the fiber gradually stabilizes between 0.96 and 0.98. This phenomenon is attributed to the Malinger effect. The Malinger effect describes stress softening and hysteresis phenomena that occur in elastic materials. Therefore, to mitigate adverse effects, each fiber used for sensing underwent at least 100 cycles of pretreatment from 0% strain to 50% strain. In fact, the pretreatment was performed at a higher strain than the maximum strain encountered by the sensor during use. The two experiments above demonstrate that the fiber exhibits extremely high stability after bending and tensile deformation, ensuring the reproducibility of the experimental results.

[0060] To compare the sensing performance of a 10cm straight optical fiber and a 10cm bent optical fiber, tensile strains ranging from 0% to 50% and then back to 0% were applied to both types of fibers at 10% elongation intervals. The relationship between the light intensity and strain passing through the fibers in both conditions was measured. Figure 5 As shown in Figure c, during the stretching process, the optical signal in the optical fiber changes simultaneously with the tensile strain, which is a necessary condition for the deformation sensor to perform its sensing task. Furthermore, compared to a straight optical fiber, the optical fiber in a folded, bent state exhibits a maximum 7-fold increase in its light response sensitivity to strain. This indicates that the folded, bent optical fiber possesses higher strain response sensitivity, which is the most important reason for mounting the optical fiber in a bent state on the glove.

[0061] To quantify the effect of stretching on the optical transmission characteristics of fiber under bending conditions, within a strain range of 0%–50%, the fiber under closed bending conditions was subjected to 50 cycles of stretching at 10°C intervals between 10°C and 50°C. The normalized spectrum of the fiber in the wavelength range of (530–690 nm) was measured after each cycle, and the average normalized light intensity at 650 nm at different temperatures was calculated. Figure 5d). As can be seen, the optical loss after cycling gradually increases with the rise in ambient temperature. However, when the ambient temperature is below 50°C, the loss of normalized light intensity does not exceed 15%. Therefore, when working in an environment with a temperature of 0–50°C, the flexible optical fiber provided in this embodiment still exhibits extremely high stability in a bent state.

[0062] In summary, changes in ambient temperature, as well as deformations such as bending, stretching, and indentation, all lead to optical transmission loss in optical fibers. When the ambient temperature is between 0 and 50°C, the loss caused by stretching deformation is relatively small, and the optical fiber can maintain its sensing performance well. Furthermore, this flexible optical fiber also exhibits high optical transmission stability after bending and indentation deformation. The ability of the optical fiber to maintain high stability after deformation and to ensure that the optical signal changes with the deformation during the deformation process is fundamental to optical fiber sensing. Most importantly, compared to a straight optical fiber, a folded optical fiber has a higher strain response sensitivity.

[0063] The present invention also discloses a data glove that uses a flexible fiber optic sensor that has undergone the above-mentioned tests.

[0064] Based on the design and data acquisition methods of the data glove, a control platform related to the data glove was also established. Here, a Raspberry Pi (RPi) robotic hand with six degrees of freedom was used. In the RPi environment, Python was used to process the grayscale information transmitted by the data glove. The processing results can be transmitted to the robotic hand in real time to achieve real-time gesture tracking. Figure 6 As shown, the data processing process of the control system of this data glove includes the following steps: preprocessing-self-calibration, data processing, robust fine-tuning, self-compensation processing, and intelligent prediction.

[0065] Because everyone's hand shape and initial light source values ​​are different, the initial state of wearing the gloves may vary each time. Therefore, it is necessary to adjust the zero-point position and amplitude of the sensor when using the data gloves. The preprocessing-self-calibration specifically includes: adjusting the zero-point position and amplitude of the sensor. During the adjustment process, the user performs a series of specific gestures in advance to obtain values ​​that match the user's hand shape, thus ensuring the stable performance of the data gloves. After preprocessing, the maximum and minimum bending gray values ​​of each finger at its limit position and the gray value in the semi-grip state are collected; the gray values ​​at the maximum and minimum bending limits can be determined as the gray value variation range. The gray value in the semi-grip state corresponds to the position point of the robotic hand, thereby obtaining a gentler mapping relationship (robotic hand servo and data glove), which is the basis of data processing. Therefore, combined with the self-calibration function that can improve the accuracy of data acquisition, the data gloves adapt to different hand shapes and bending habits; this makes the "user-friendly" data gloves customizable according to the user's needs.

[0066] Data processing specifically includes: transmitting the mapping relationship between grayscale values ​​and specific gestures to the system for automatic calibration; linking the pre-processed mapping relationship with the servo motor of the controller to construct a new mapping relationship; after pre-processing, the data glove outputs five grayscale values ​​in real time (corresponding to the five fingers). Based on the five real-time grayscale values, they are transferred to the robotic hand through the mapping relationship in the system to achieve real-time gesture tracking; every time the user of the data glove makes a hand movement, the robotic hand will make a corresponding movement in real time.

[0067] In the process of acquiring and processing glove data, the real-time performance, accuracy, and robustness of the control system are key factors in evaluating system performance. During gesture tracking, the system needs to respond promptly and accurately transmit data to the robotic hand; therefore, a reasonable and effective algorithm is essential. Maintaining stable robustness in the face of abnormal situations is also crucial. Robustness fine-tuning specifically includes: during glove use, to prevent mapping deviations caused by inaccurate maximum and minimum grayscale values ​​and amplitudes obtained in the preprocessing stage, the mapping relationship was fine-tuned three times. To ensure stable robustness, in the event of abnormal situations, such as sudden changes in values ​​due to external force on the data glove, a series of judgments and settings are required before fine-tuning the mapping relationship. When the value exceeds or falls below 50% of the original limit point, the system will statistically analyze such extreme cases. Adjustment is only made after five instances of fluctuations within 5% of the limit value.

[0068] During the use of data gloves, it is difficult to replace the batteries in a timely manner. Therefore, as the battery power gradually decreases, the current intensity flowing to the light source decreases, leading to a weakening of the emitted light. This directly reduces the light in the optical fiber, resulting in the data acquisition camera capturing a cross-sectional grayscale value lower than the theoretical value. This significantly increases the error in the gesture capture experiment. To compensate for this error caused by battery aging, an additional 5cm communication-grade plastic optical fiber (attenuation less than 180dB / km) is installed between the light source and the data acquisition camera as a control. The self-compensation processing specifically includes: in grayscale images, brightness is equivalent to grayscale. By correcting the grayscale, this proportional decrease is eliminated, and a corrected grayscale value close to the theoretical value is obtained.

[0069] The specific formula for the self-compensation process is as follows:

[0070]

[0071] Where I0 represents the initial luminance of the plastic reference fiber cross-section, approximately equal to the initial luminance of the light source; I r The real-time luminance of the plastic reference fiber cross-section is approximately equal to the real-time luminance of the light source; when i = 1, 2, 3, 4, 5, L i and I i These represent the initial and real-time luminous intensity of the fiber cross-section corresponding to each finger, respectively.

[0072] In the design of the data glove, five sensing optical fibers and a plastic reference fiber are installed between the same data acquisition camera and the same light source. When the brightness of the light source decreases during sensor application, the cross-sectional brightness of the five sensing optical fibers decreases proportionally with the brightness of the light source. This proportional decrease can be eliminated by conversion using formula (1), and a corrected grayscale value close to the theoretical value can be obtained. This compensates for experimental errors caused by battery aging during the use of the data glove, which is extremely important for providing users with a good experience.

[0073] Because the hand contains muscles, skin, and other soft tissues, the movement of one finger can affect the output of adjacent, otherwise inactive, sensors, causing the robotic hand to make erroneous movements. Given this phenomenon, we conducted numerous tests on gesture capture and discovered that it follows a pattern. For example, when the middle finger is bent, the corresponding sensors will react even if the ring and index fingers are still. Intelligent prediction specifically involves collecting various similar patterns through extensive testing and data analysis, forming a motion-related prediction library. Based on these error patterns, a compensation function can be derived to mitigate misjudgments of fluctuations. Real-time data response is extremely important in the data processing process, directly affecting the real-time tracking of gestures and the user experience of the glove. In this work, the real-time data response primarily depends on the frame rate of the grayscale values ​​of the flexible fiber cross-section captured by the camera. An 8-megapixel camera with a dynamic frame rate of 25fps–30fps can capture data 18 times per second, containing 90 data points, which is sufficient to provide a good user experience.

[0074] like Figure 7 As shown, the data glove's interface can connect to the robotic arm's Raspberry Pi control panel. The robotic arm uses the acquired grayscale values ​​as commands to perform the same gestures as the data glove. The data glove's sensing performance was tested in two states: static and dynamic. The static test observed whether the cross-sectional grayscale value of the optical fiber changed accordingly when the data glove made a gesture, to better understand the accuracy of the flexible optical fiber's quantization of finger bending. The dynamic test evaluated the data glove's real-time performance and stability by capturing the gesture tracking effect of the robotic arm.

[0075] In static testing, six consecutive actions were captured to observe the changes in grayscale values ​​of the flexible optical fiber under different hand gestures. For example... Figure 7 As shown, during gesture changes, the corresponding curve changes are clearly observable. The bending of the finger causes the flexible optical fiber to experience tension and pressure from both the latex tube and the bent knuckle. Fiber deformation leads to radiation loss, resulting in a decrease in the brightness of the flexible fiber's cross-section, and the grayscale value also decreases accordingly. When the finger gradually extends, the pressure on the fiber decreases, and the grayscale value returns to its initial value. When the gesture remains in one position, the grayscale value remains unchanged. Due to differences in the length of the flexible optical fiber and the varying encapsulation force of the encapsulation material, the grayscale value range varies. However, this difference is only reflected in the maximum and minimum values ​​of the grayscale value; each flexible optical fiber follows almost the same overall trend.

[0076] It's worth noting that when one finger bends, the corresponding curves of other fingers may also fluctuate, rather than remaining a straight line as expected. This is due to the physiological structure of the hand. The movements of the finger joints are not independent. There is a correlation between the fingers when making different gestures. However, the related fluctuations are not sharp enough to affect the use of data gloves.

[0077] To observe the process of quantizing the flexible fiber optic finger more closely, the index finger was selected as a representative, and six extension amplitudes were selected, from clenching-extension-clenching, with the extension amplitude gradually increasing until it was fully extended. Figure 6 As can be seen, with the stepwise increase in finger extension, the corresponding grayscale value also gradually increases stepwise. Furthermore, when using data gloves, the flexible optical fiber is repeatedly subjected to the pressure caused by bending. Therefore, verifying whether the flexible optical fiber can maintain high stability within the glove is equally important. The index finger was selected, and the bending-stretching process was repeated 50 times, observing the maximum and minimum grayscale values. Figure 6 As can be seen, after 50 transformations, the maximum and minimum values ​​of the grayscale remain within a stable range.

[0078] To evaluate the timeliness and repeatability of the data glove, the actions performed in the static test were repeatedly executed using the data glove in a dynamic test. The robotic arm tracked the continuous movement of each finger in real time. It was observed that the data glove could accurately recognize each gesture and respond quickly during the dynamic process, thereby guiding the robotic arm to perform corresponding actions and achieving rapid human-machine interaction. The time delay of the data glove was measured; the time from the start of the data glove's action to the completion of the subsequent action by the robotic arm was approximately 0.4 seconds. The time delay can be further reduced by increasing the light signal acquisition frequency to capture more points. Therefore, the data glove provided in this embodiment can fully meet the requirements for real-time interaction with the robotic arm.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for manufacturing a flexible fiber optic sensor for use in data gloves, characterized in that, The flexible fiber optic sensor includes a flexible fiber, a light source, a power supply, a miniature camera, and an external package encapsulating the above components. The power supply is connected to the light source. The miniature camera is used to collect changes in the grayscale value of the flexible fiber cross-section. A reference fiber is provided between the light source and the miniature camera to compensate for changes in light intensity caused by a decrease in power during use. The flexible fiber is U-shaped and its length exceeds the length of a finger. It is folded in half by a shaft and embedded in a latex tube. The latex tube is then bonded to the data glove by indirect adhesive. The production method includes the following steps: Step 1: Prepare the liquid materials for the core layer and the cladding layer, defoam the liquid materials, and inject the defoamed liquids into syringes A and B respectively; Step 2: Spray a layer of oily release agent onto the mold. After the release agent dries, place the heat shrink tubing into the hollow tube and fix the heat shrink tubing in the center of the hollow tube with a positioning plug. Step 3: Use syringe A to inject the defoaming cladding solution into the interlayer between the acrylic tube and the heat shrink tube. After standing for a period of time, place it in a drying oven to cure. Then, raise the temperature and adjust the diameter of the heat shrink tube to the preset value before pulling it out. The cladding solution forms a stretchable transparent hollow tube as the cladding of the flexible optical fiber. Step 4: Inject the defoamed core solution into the cladding using syringe B, let it stand for a period of time, then place it in a drying oven to cure, and pull the flexible optical fiber out of the hollow tube.

2. The manufacturing method according to claim 1, characterized in that, The flexible optical fiber is composed of a double-layer coaxial cylindrical rubber structure. The core material is a two-component RTV silicone rubber, and the cladding material is a two-component addition-type liquid silicone rubber.

3. The manufacturing method according to claim 1, characterized in that, The flexible optical fiber is mounted on the data glove with a bending radius of 5±1mm.

4. The manufacturing method according to claim 1, characterized in that, The testing methods for the flexible fiber optic sensor include bending tests, tensile tests, and indentation tests.

5. The manufacturing method according to claim 4, characterized in that, The specific testing method includes the following steps: The bending radius-normalized light intensity relationship diagram at the corresponding wavelength is determined based on the selected light source. By sequentially increasing the tensile strain, the strain-normalized light intensity relationship of the optical fiber was measured. Measure the length-normalized light intensity relationship of optical fibers of different lengths; Different pressures were applied sequentially to the side of the optical fiber to obtain pressure-normalized light intensity curves. The optical fiber was repeatedly bent from a straight state to a bent state, and the normalized spectrum of the optical fiber was measured after a preset number of times. The tensile strain of the optical fiber was repeatedly adjusted, and the normalized spectrum of the optical fiber was measured after a preset number of times. Under the premise of repeatedly adjusting the tensile strain of the optical fiber, the sensing performance of a straight optical fiber of the same length and a folded optical fiber were compared. Under the premise of repeatedly adjusting the tensile strain of the optical fiber, the average normalized light intensity of the optical fiber was measured a preset number of times at different temperatures.

6. A data glove employing a flexible fiber optic sensor tested according to claim 5.

7. The data glove according to claim 6, characterized in that, The data processing of the control system of this data glove includes the following steps: preprocessing-self-calibration, data processing, robust fine-tuning, self-compensation processing, and intelligent prediction. The preprocessing-self-calibration specifically includes: adjusting the zero point position and amplitude of the sensor. During the adjustment process, the user performs a series of specific gestures in advance to obtain values ​​that match the user's hand shape. After preprocessing, the maximum and minimum bending gray values ​​of each finger at the extreme position and the gray value in the half-grip state are collected. The data glove adapts to different hand shapes and bending habits. The data processing specifically includes: transmitting the mapping relationship between grayscale values ​​and specific gestures to the system for automatic calibration; linking the pre-processed mapping relationship with the servo motor of the manipulator to construct a new mapping relationship; and transferring the five real-time grayscale values ​​to the robotic hand through the mapping relationship in the system to achieve real-time gesture tracking. Robust fine-tuning specifically includes: the system statistically analyzes the extreme values ​​encountered based on abnormal situations, and performs robust fine-tuning after exceeding a preset number of times; The self-compensation processing specifically includes: when the brightness of the light source decreases during sensor application due to power supply issues, the cross-sectional brightness of the five reference optical fibers will decrease proportionally along with the brightness of the light source. This proportional decrease is eliminated by correcting the grayscale, and a corrected grayscale value close to the theoretical value is obtained. The intelligent prediction process involves: acquiring data on the impact of a moving finger on adjacent fingers, constructing a prediction library related to the movement, and obtaining a compensation function relationship based on the error patterns in the prediction library.

8. The data glove according to claim 7, characterized in that, The specific formula for the self-compensation process is as follows: Correct grayscale ( i = 1,2,3,4,5)(1) Where I0 represents the initial luminance of the plastic reference fiber cross-section, approximately equal to the initial luminance of the light source; I r The real-time luminance of the plastic reference fiber cross-section is approximately equal to the real-time luminance of the light source; when i = 1,2,3,4,5, L i and I i These represent the initial and real-time luminous intensity of the fiber cross-section corresponding to each finger, respectively.

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