Wearable devices and methods implemented at wearable devices

Abstract

Disclosed is wearable device (WD) (100) that in use, to be worn around neck of user, comprising: first set (102A) and second set (102B) of obstacle sensors arranged in first end portion (104) and second end portion (106) of WD respectively, wherein a given set of OS comprises given Time-of-Flight (ToF) sensor(s) (108, 112) and given ultrasonic (US) sensor(s) (110, 114), providing predefined field of view (FOV) for object detection around WD; set of haptic actuators (HAs); and processor(s) configured to: process first sensor data, detect whether object is present in predefined FOV; when detected that object is present in predefined FOV, determine direction of object with respect to user, and control HAs to provide haptic feedback indicative of at least presence of object in predefined FOV and direction of object, to user. The set of HAs comprises rear HA(s) (116), first side HA(s) (120), and second HA(s) (124).

Description

[0001] WEARABLE DEVICES AND METHODS IMPLEMENTED AT WEARABLE DEVICES

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wearable devices that while in use, are to be worn around the neck of users. Moreover, the present disclosure relates to methods implemented at wearable devices.

[0004] BACKGROUND

[0005] In recent times, the demand for wearable hazard detection devices has grown significantly, driven by a need for the improved safety and awareness of visually-impaired individuals in various environments. Typically, the increasing complexity of modern urban landscapes, coupled with the rise of dynamic work and recreational activities, has highlighted the essential importance of real-time hazard awareness for the visually- impaired individuals navigating these diverse settings. Whether in construction sites, busy urban areas, or outdoor recreational spaces, the ability to detect and mitigate potential hazards is essential for minimizing risks and enhancing the overall safety of the visually-impaired individuals. However, existing wearable hazard detection devices face challenges related to accuracy, portability, and user interface design, particularly with regards to delivering real-time hazard information to users without overwhelming their cognitive load. Therefore, there is a focus on developing technologies that enhance the integration of sensor components and design with wearable devices while overcoming said challenges.

[0006] However, existing wearable hazard detection devices are associated with several limitations. Firstly, the wearable hazard detection devices (for example, such as chest-centric hazard detection devices) utilizing Infrared Time-of-Flight (IR ToF) sensors have limited use in bright light conditions. This is so because the IR. ToF sensors become overwhelmed by excessive infrared radiation reflecting back from natural daylight and reflective surfaces (such as glass), thereby leading to inaccurate and unreliable performance. This adversely impacts the overall performance, accuracy, and durability of the wearable hazard detection devices utilizing IR ToF sensors. Furthermore, the chest-centric hazard detection devices, for example, are uncomfortable to wear and can be stigmatising, and thus are not easily adopted widely.

[0007] Secondly, wearable hazard detection devices (for example, such as wristband hazard detection devices, smart cane hazard detection devices and haptic shoes hazard detection devices) utilizing ultrasonic (US) sensors face challenges with detecting certain types of objects. Typically, soft objects tend to absorb ultrasonic waves, thus making the object difficult to detect with US sensors , while thin cylindrical objects and / or angled surfaces can reflect the ultrasonic waves at oblique angles, hence resulting in missed detections. Furthermore, wristband hazard detection devices, for example, have a poor field of view and use a single US sensor which provides inaccurate distance measurements and unreliable obstacle detection. Similarly, smart cane hazard detection devices also have a poor field of view and are frequently damaged due to their contact with various surfaces. Such smart cane hazard detection devices also use a single US sensor which can provide inaccurate distance measurements and unreliable obstacle detection due to limitations in coverage and / or sensitivity to environmental factors. Furthermore, haptic shoes hazard detection devices are limited to detecting hazards typically identified by a cane, necessitating the use of specialized footwear, which can sometimes be stigmatizing for users. Therefore, such haptic shoes hazard detection devices are not easily adopted widely.

[0008] Computer vision systems are widely used for hazard detection when implemented in wearable hazard detection devices (for example, such as in smart glasses and smart harnesses) but have notable limitations. These computer vision systems are prone to false positives because their logic comprises multiple failure modes. Specifically, the computer vision systems determine depth by analysing the disparity between two images, a process that can be easily deceived by two-dimensional (2D) representations of three-dimensional (3D) spaces. Additionally, computer vision systems rely heavily on detecting edges and surface details. As a result, a blank wall or a large featureless object may be misinterpreted as not being present, hence leading to detection failures. Furthermore, smart glasses utilizing the computer vision systems are often heavy and bulky, exhibit short battery life, perform poorly in low light conditions, have intrusive forehead haptics, are head-worn, and can be stigmatizing for users. Similarly, smart harnesses utilizing the computer vision systems and / or self-driving artificial intelligence (Al) are also heavy and bulky, exhibit short battery life, provide audio-only feedback, and can be stigmatizing for users. Therefore such devices are also not easily adopted widely.

[0009] To achieve highly reliable data, computer vision systems often use stereo video imagery to create depth maps. This process involves capturing and processing images multiple times per second, resulting in complex algorithms, heavy computational loads, and high-power demands to support the necessary processing power. This is processor intensive and time consuming. Hence, these limitations highlight the need for more efficient and reliable hazard detection solutions that can perform consistently across various environmental conditions.

[0010] Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks. SUMMARY

[0011] The aim of the present disclosure is to provide a wearable device that, while in use, is to be worn around the neck of a user, and a method implemented at the wearable device to provide enhanced object detection for the user. The aim of the present disclosure is achieved by a wearable device that, while in use, is to be worn around the neck of a user and a method implemented at the wearable device as defined in the appended independent claims to which reference is made to. Advantageous features are set out in the appended dependent claims.

[0012] Throughout the description and claims of this specification, the words "comprise" , "include", "have", and "contain" and variations of these words, for example "comprising" and "comprises" , mean "including but not limited to", and do not exclude other components, items, integers or steps not explicitly disclosed also to be present. Moreover, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

[0013] BRIEF DESCRIPTION OF THE DRAWINGS

[0014] FIG. 1A illustrates a perspective view of a wearable device, and FIG. IB illustrates a side view of a wearable device, in accordance with an embodiment of the present disclosure;

[0015] FIG. 2 illustrates a predefined field of view (FOV) of a wearable device, in accordance with an embodiment of the present disclosure;

[0016] FIG. 3 illustrates a graphical representation of performance of a Time-of- Flight sensor and an ultrasonic sensor, in accordance with an embodiment of the present disclosure; and FIG. 4 illustrates steps of a method implemented at a wearable device, in accordance with an embodiment of the present disclosure.

[0017] DETAILED DESCRIPTION OF EMBODIMENTS

[0018] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practising the present disclosure are also possible.

[0019] In a first aspect, the present disclosure provides a wearable device that in use, is to be worn around a neck of a user, the wearable device comprising: a first set of obstacle sensors arranged in a first end portion of the wearable device, wherein the first set of obstacle sensors comprises at least one first Time-of-Flight (ToF) sensor and at least one first ultrasonic sensor; a second set of obstacle sensors arranged in a second end portion of the wearable device, wherein the second set of obstacle sensors comprises at least one second ToF sensor and at least one second ultrasonic sensor, and wherein the first set of obstacle sensors and the second set of obstacle sensors provide a predefined field of view (FOV) for object detection around the wearable device; a set of haptic actuators comprising at least one rear haptic actuator arranged in a neckband of the wearable device, at least one first side haptic actuator arranged in a first side portion of the wearable device that lies between the neckband and the first end portion, and at least one second side haptic actuator arranged in a second side portion of the wearable device that lies between the neckband and the second end portion; and at least one processor configured to: process first sensor data, collected by the first set of obstacle sensors and the second set of obstacle sensors, to detect whether an object is present in the predefined FOV; when it is detected that the object is present in the predefined FOV, determine a direction of the object with respect to the user, based on the first sensor data, and control the set of haptic actuators to provide a haptic feedback indicative of at least the presence of the object in the predefined FOV and the direction of the object, to the user.

[0020] In a second aspect, the present disclosure provides a method implemented at the wearable device of any of the preceding claims, the method comprising : processing first sensor data, collected by the first set of obstacle sensors and the second set of obstacle sensors, for detecting whether an object is present in a predefined FOV, wherein the predefined FOV is provided, by the first set of obstacle sensors and the second set of obstacle sensors, for object detection around the wearable device; when it is detected that the object is present in the predefined FOV, determining a direction of the object with respect to the user, based on the first sensor data, and controlling the set of haptic actuators to provide a haptic feedback indicative of at least the presence of the object in the predefined FOV and the direction of the object, to the user. The present disclosure provides the aforementioned first aspect and the aforementioned second aspect of detecting objects for the user who is visually-impaired. Herein, the wearable device utilizes twin-sensor technology, wherein the wearable device comprises the at least one first and second ToF sensors and the at least one first and second ultrasonic sensors. Such twin-sensor technology facilitates detection of objects in any condition, as the ToF sensors and the ultrasonic sensors complement each other's shortcomings to work across a range of conditions that either technology on its own cannot handle. The first sensor data is highly reliable data which is collected without a full analysis of the environment (namely, surroundings) around the user wearing the wearable device. The wearable device comprises the first set of obstacle sensors and the second set of obstacle sensors to provide object detection with no false alerts. The set of haptic actuators provides intuitive and streamlined interaction to navigate the user. Moreover, the wearable device is light in weight, a single structure, comfortable wearable format, which can be worn for prolonged periods around the neck. The wearable device and the method facilitate a user-friendly, simple and effective way of object detection.

[0021] The term "wearable device" refers to an electronic device that is designed to assist the user who could be suffering from visual impairment, by enhancing a spatial awareness of the user. Herein, the wearable device is implemented using wearable technology. The wearable device is configured in a manner that, when in use, said wearable device facilitates detection of objects. The wearable device is worn around the neck to provide a stable and secure position, as there is minimal to no movement which ensures consistent alignment of different sensors and haptic actuators. Notably, the wearable device is in the form of a neckband to facilitate ease of wearing and maintenance. Moreover, the wearable device is rugged in design which does not clash with a preference of the user. The wearable device being worn around the neck renders the hands of the user free, thus allowing the user to perform other tasks without obstruction.

[0022] Throughout the present disclosure, the term "obstacle sensor" refers to an electronic device that is designed to at least detect objects within the predefined FOV (as explained later) of a given set of obstacle sensors. Herein, arrangement of the given set of obstacle sensors in a given end portion of the wearable device ensures that potential objects are detected early. A technical effect of using the given set of obstacle sensors is that there is a wide-angle FOV available, and there is redundancy for the object detection. Additionally, such arrangement facilitates continuous monitoring of immediate surroundings of the user, which enables the user to navigate in a safe manner. Furthermore, such arrangement of the given set of obstacle sensors integrates seamlessly with an overall form factor of the wearable device, thus ensuring protection of the given set of obstacle sensors while avoiding interference with comfort or mobility of the user.

[0023] Herein, the term "given set of obstacle sensors" encompasses the first set of obstacle sensors and the second set of obstacle sensors, and the term "given end portion" encompasses the first end portion and the second end portion. Moreover, the term "end portion" refers to a front section of the wearable device on a particular side of the neck, when the wearable device is worn around the neck. In this regard, the first end portion is arranged on any one of a left side or a right side of a neck of the user, and the second end portion is arranged on another one of the right side or the left side of the neck of the user.

[0024] Throughout the present disclosure, the term "Time-of-Flight sensor" refers to a sensor that emits infrared light and detects the infrared light upon reflection from surface and / or objects. Herein, at least one of: an intensity, an angle, of the reflected infrared light is used for detection of the objects. Throughout the present disclosure, the term "ultrasonic sensor" refers to a sensor that emits high-frequency waves and measures a time taken for said high-frequency waves to bounce back after hitting the surfaces and / or the objects. In this regard, a delay in time taken for the high-frequency waves to bounce back is used to determine detection and / or calculation of distances of surfaces and / or the objects. The least one given Time-of-Flight (ToF) sensor and at least one given ultrasonic sensor are arranged in a form of one-dimensional (ID) array or a two- dimensional array (2D) in the wearable device.

[0025] The given set of obstacle sensors comprises the at least one given Time- of-Flight (ToF) sensor and at least one given ultrasonic sensor to complement each other's shortcomings to work across a range of conditions that the at least one given ToF sensor and the at least one given ultrasonic sensor cannot on its own. Herein, the term "at least one given Time-of-Flight (ToF) sensor" encompasses the at least one first ToF sensor and the at least one second ToF sensor, and the term "at least one given ultrasonic sensor" encompasses the at least one first ultrasonic sensor and the at least one second ultrasonic sensor. Moreover, a performance of the at least one given ultrasonic sensor is unaffected for following conditions: an intensity of ambient light, a transmission of the ambient light, an absorption of the ambient light by the object, an amount of scattering of the ambient light. A performance of the at least one given ToF sensor is unaffected for following conditions: a geometry, a material, provided the material is not transparent or black in colour, an angle of the surfaces and / or objects. The marginal ability of the ToF to detect materials that are black or transparent is mitigated by the US, as US bounces back well off the hard front surface of glass, and is not affected by colour. As an example, the performance of the at least one given ultrasonic sensor may be unaffected for any of the following conditions: high ambient light level, a transparent object, a dark object. A performance of the at least one given ToF sensor may be unaffected for any of following conditions: opaque curved objects, uneven surfaces, angled surfaces. However, the performance of the at least one given ultrasonic sensor may be good for the condition of opaque curved objects, and marginal for at least one of the following conditions: the uneven surfaces, the angled surfaces, the soft objects. The performance of at least one given ToF sensor may be poor for the condition of the high ambient light level, marginal for the condition of the transparent objects, good for at least one of the following conditions: the dark objects, the soft objects.

[0026] Throughout the present disclosure, the term "field of view" refers to a spatial region or an angular region in which the given set of obstacle sensors can effectively detect the objects. Moreover, the FOV defines boundaries of an area that the given set of obstacle sensors can monitor for the object detection. The term "predefined FOV" refers to a predetermined FOV that is fixed during a configuration of the wearable device. In this regard, the at least one given obstacle sensor is positioned and calibrated to cover a particular spatial region or particular angular region around the wearable device.

[0027] Optionally, the predefined FOV spans at least 180 degrees horizontal FOV. In this regard, the predefined FOV of the wearable device covers at least 180 degrees horizontally, enabling it to detect obstacles across a wide horizontal range. For example, the predefined FOV may be 180 degrees, 182 degrees, 184 degrees, 186 degrees, 190 degrees, 195, 200 degrees and so forth. Preferably the FOV is at an angle of 145 degrees. This predefined FOV provides a wide coverage that enables comprehensive object detection around the user. The predefined FOV ensures that the wearable device can alert the user about potential hazards not just directly in front, but also around the sides of the user, thus enhancing safety and situational awareness, especially for users that are visually-impaired. Optionally, the predefined FOV spans at least 90 degrees vertical FOV. In other words, the predefined FOV provides a vertical head to knee coverage.

[0028] Beneficially, the predefined FOV of the wearable device is greater than an FOV of a cane (which is a most popularly used assistance device by visually impaired people). Thereby, the wide FOV ensures that missing areas are also monitored, thus providing more reliable object detection. Herein, the wearable device achieves the predefined FOV of at least 180 degrees horizontal FOV by placing the given set of obstacle sensors in a strategic manner. Thereby, the at least one processor integrates data from the set of obstacle sensors to create a seamless and extensive horizontal view and optionally vertical view, enabling for effective object detection within this range.

[0029] A technical effect of the predefined FOV spanning at least 180 degrees horizontal FOV is that since the wearable device is able to detect obstacles in a very wide FOV, the wearable device is able to detect a large number of objects (including, for example, even those objects which the cane typically misses to detect). As a result, the wearable device provides highly accurate object detection for improving a feeling of safety amongst the users that are visually-impaired.

[0030] Optionally, the predefined FOV comprises: a first side peripheral zone defined by an FOV of at least one obstacle sensor in the first set of obstacle sensors, a second side peripheral zone defined by an FOV of at least one obstacle sensor in the second set of obstacle sensors, and a central zone defined by a combined FOV of one or more obstacle sensors in the first set of obstacle sensors and one or more obstacle sensors in the second set of obstacle sensors. In this regard, the predefined FOV is divided into zones to effectively detect objects in a wide spatial region surrounding the user, when the wearable device is in use. A technical effect of the predefined FOV comprising such zones is that there is comprehensive coverage of the surrounding environment of the user, thereby allowing the at least one given set of obstacle sensors to detect objects or potential hazards in direct line-of-sight of the user and in peripheral sight of the user.

[0031] Herein, the term "side peripheral zone" refers to the spatial region to a particular side of the wearable device. Herein, the side peripheral zone allows the wearable device to detect the objects situated to a side or periphery of a view of the user. As a first example, the first end portion where the first set of obstacle sensors is arranged may be on the left side of the neck, and the second end portion where the second set of obstacle sensors is arranged may be on the right side of the neck. Hence, the first side peripheral zone may be defined by a left side FOV of the user, and the second side peripheral zone may be defined by a right side FOV of the user.

[0032] Moreover, the term "central zone" refers to the spatial region directly in front of the wearable device. Herein, the one or more obstacle sensors in the first set of obstacle sensors and one or more obstacle sensors in the second set of obstacle sensors have different FOVs, wherein the different FOVs overlap at a center of the one or more obstacle sensors in the first set of obstacle sensors and the one or more obstacle sensors in the second set of obstacle sensors, thus providing the combined FOV. In this regard, the FOV of the one or more obstacle sensors in the first set of obstacle sensors may at least partially overlap with an FOV of the one or more obstacle sensors in the second set of obstacle sensors, to produce the combined FOV.

[0033] Optionally, the predefined FOV also comprises at least one of: a first intermediate zone between the first side peripheral zone and the central zone, a second intermediate zone between the second side peripheral zone and the central zone. Herein, the first intermediate zone may or may not have overlapping FOVs of the at least one obstacle sensor and the one or more obstacle sensors in the first set of obstacle sensors. Similarly, the second intermediate zone may or may not have overlapping FOVs of the at least one obstacle sensor and the one or more obstacle sensors in the second set of obstacle sensors.

[0034] Optionally, the predefined FOV of the first set of obstacle sensors and second set of obstacle sensors comprises an exclusion area. Herein, the exclusion area excludes a predefined portion around the body of the user. The predefined portion lies in a range from 0.1 metre to 0.5 metre from the body of the user. This exclusion area prevents alerts triggered by the user's hands which may pass across, or be present within a FOV of the wearable device when worn around the neck. The first and second set of obstacle sensor data is checked to see if an object within the exclusion zone was previously detected within an active FOV area before entering the exclusion zone to determine if that object is approaching, and may present a hazard to the user, or if it has suddenly appeared. If a new object is detected without previous detection in an active FOV area, an alert is given to the user after a delay of 0.1 to 2 seconds, preferably 2 seconds, as the object is assumed to be the user's hand, or a similar object. If the object persists in the exclusion area, then the alert is triggered with a special sound. This is due to the object (eg. the user's hand) blocking detection of other approaching objects. Moreover, sensing of objects very close (for example, less than 0.1m from the sensors) to the first set of obstacle sensors and the second set of obstacle sensors, enables detection objects, for example, such as, items of clothing or long hair of the user, that may be in front of the first set of obstacle sensors and the second set of obstacle sensors and will always alert the user. Such objects block the FOV of the first set of obstacle sensors and the second set of obstacle sensors. The 3 m outer boundary of the exclusion area that is active could be adjusted by the user to increase or decrease this outer boundary depending on a situational context of the user wearing the wearable device.

[0035] For example, an exemplary situational context may be, walking fast outdoors when there are less objects as compared to walking indoors when there are more objects. Herein, walking fast when outdoors when there are less objects may be best suited to longer range sensing, and walking indoors when there are more objects, for example, such as in train stations or crowded spaces, an exemplary range of the first and the second set of obstacle sensors can be limited for a lesser distance such as lm. The central zone covers the horizontal area directly in front of the user, extending from the user outward with the exclusion area, in the same manner as described for the first side peripheral zone and the second side peripheral zone.

[0036] Throughout the present disclosure, the term "haptic actuator" refers to a device that provides tactile feedback and / or vibrotactile feedback, to provide a sense of touch or physical sensation to the user. The term "at least one rear haptic actuator" refers to one or more haptic actuators positioned in the neckband portion of the wearable device. The at least one rear haptic actuator provides the tactile feedback and / or vibrotactile feedback at the back of the user's neck, where the neckband is arranged. Moreover, the at least one first side haptic actuator provides the tactile feedback and / or vibrotactile feedback via the first side portion to indicate that the object has been detected on that particular side. The at least one second side haptic actuator provides the tactile feedback and / or vibrotactile feedback via the second side portion to indicate that the object has been detected on that particular side. When the wearable device is worn by the user, the first side portion lies on at least one of: a side of a neck of the user, a collarbone of the user, a chest of the user. Similarly, the second side portion lies on at least one of: another side of a neck of the user, another collarbone of the user, the chest of the user. A technical effect of such placement of the set of haptic actuators in different regions of the wearable device allows for delivering the tactile feedback and / or the vibrotactile feedback from a particular direction.

[0037] Continuing in reference with the first example, the first side portion where the at least one first side haptic actuator may be arranged is on the left side of the neck of the user, and the second side portion where the at least one second side haptic actuator may be arranged is on the right side of the neck of the user.

[0038] It will be appreciated that the at least one processor is communicably coupled with the first set of obstacle sensors, the second set of obstacle sensors, and the set of haptic actuators. The at least one processor could be implemented as any one of: a microprocessor, a microcontroller, or a controller. As an example, the at least one processor could be implemented as an application-specific integrated circuit (ASIC) chip or a reduced instruction set computer (RISC) chip.

[0039] It will be appreciated that the object detection could be performed without a user device (for example, such as a mobile phone) associated with the user, as the wearable device comprises all hardware, i.e., the first set of obstacle sensors, the second set of obstacle sensors, the set of haptic actuators, the at least one processor, and optionally, a rechargeable battery, on-board. Moreover, the wearable device can be turned on or turned off for the object detection, as per user requirements.

[0040] The first set of obstacle sensors and the second set of obstacle sensors collect the first sensor data about their respective surroundings in the predefined FOV. In this regard, the at least one processor is configured to combine data received from the first set of obstacle sensors and the second set of obstacle sensors, to generate the first sensor data. Optionally, each data received from the first set of obstacle sensors and the second set of obstacle sensors is combined to form the first sensor data, wherein the at least one processor is configured to: align each data based on positions and orientations of the first set of obstacle sensors and the second set of obstacle sensors, and correlate data points to identify consistent measurements from the first set of obstacle sensors and the second set of obstacle sensors.

[0041] The first sensor data is collected by the at least one processor in a continuous manner or a near-continuous manner. Moreover, the first sensor data could be in various forms, for example, such as distance measurements, depth information, and similar. The first sensor data is processed using processing algorithms to analyse the first sensor data to identify at least one of: a pattern, a change, an anomaly, that may indicate the presence of the object within the predefined FOV. Such processing algorithms are well-known in the art. Moreover, upon such detection, the at least one processor may optionally be further configured to classify or identify a type of object based on additional analysis. Herein, such additional analysis may include, but are not limited to, shape recognition, size estimation, and pattern matching, of the object. Hence, the at least one processor is configured to detect accurately the presence of the object within the predefined FOV, thus enabling the wearable device to provide timely alerts and / or guidance to the user. Notably, an accuracy of the first sensor data is impacted by at least one of: an environmental condition in the predefined FOV, a lighting condition in the predefined FOV, a shape of the object, a geometry of the object, a material type of the object.

[0042] Optionally, when processing the first sensor data, the at least one processor is configured to: determine whether a level of confidence associated with a first portion of the first sensor data lies below a first predefined threshold, wherein the first portion of the first sensor data is collected by the at least one first ToF sensor and the at least one second ToF sensor; when it is determined that the level of confidence associated with the first portion of the first sensor data lies below the first predefined threshold, prioritize utilization of a second portion of the first sensor data for detecting whether the object is present in the predefined FOV, wherein the second portion of the first sensor data is collected by the at least one first ultrasonic sensor and the at least one second ultrasonic sensor; and when it is determined that the level of confidence associated with the first portion of the first sensor data is equal to or lies above the first predefined threshold, prioritize utilization of the first portion of the first sensor data for detecting whether the object is present in the predefined FOV.

[0043] In this regard, the first sensor data is processed using either-or logic. A technical effect of processing the first sensor data in such a manner accurate object detection is ensured in an adaptive manner, wherein different portions of the first sensor data are prioritized in a dynamic manner.

[0044] Herein, processing the first sensor data involves evaluating the level of confidence of different portions within the first sensor data, and prioritizing use of either the at least one given ToF sensor or the at least one given ultrasonic sensor based on the level of confidence. Herein, the first sensor data is divided into the first portion and the second portion, wherein the first portion of the first sensor data comprises data collected from the at least one given ToF sensor, and the second portion of the first sensor data comprises data collected from the at least one given ultrasonic sensor. Herein, the term "level of confidence" refers to a qualitative measure that indicates how reliable the first portion of the first sensor data is, as collected by the at least one given ToF sensor in the given set of obstacle sensors. The level of confidence may be expressed as a percentage or probability. The term "first predefined threshold" refers to a level used to assess the reliability of the first portion of the first sensor data. Herein, the first predefined threshold is based on at least one of: a type of the at least one given ToF sensor, a type of the at least one given ultrasonic sensor, a specification of the at least one given ToF sensor, a specification of the at least one given ultrasonic sensor. Such predefined threshold can be programmed while manufacturing the wearable device. When the level of confidence is below the first predefined threshold, the first portion of the first sensor data is considered to be unreliable, or could require further validation. Such further validation is provided using the at least one given ultrasonic sensor.

[0045] When it is determined that the level of confidence associated with the at least one given ToF sensor lies below the first predefined threshold, the at least one processor is configured to shift focus to the second portion of the first sensor data collected by the at least one given ultrasonic sensor. In this regard, a principle employed is to use the at least one given ToF sensor to monitor light levels. When light levels are high (for example, such as a bright sunny day), the at least one given ToF sensor may detect the object in the predefined FOV, but the first portion of the first sensor data is qualified with addition of the level of confidence. Subsequently, a predefined score for the level of confidence may be defined based on characteristics and / or capability of the at least one given ToF sensors.

[0046] Moreover, upon shifting the focus to the second portion of the first sensor data, said second portion of the first sensor data is analysed and prioritised for object detection in the predefined FOV. In this regard, the second portion of the first sensor data comprises information gathered by the at least one given ultrasonic sensor. Herein, the at least one given ultrasonic sensor provides an alternative source of data that might be less affected by certain conditions impacting the at least one given ToF sensor.

[0047] If the level of confidence of the first portion of the first sensor data is equal to or above the first predefined threshold, the at least one processor continues to use the first portion for object detection. In this regard, the first portion of the first sensor data is prioritized and remains a primary source of data when the level of confidence meets or exceeds the first predefined threshold, indicating that the first portion of the first sensor data is reliable and accurate.

[0048] The wearable device detects the presence of the object within the predefined FOV using the first sensor data. The at least one processor is configured to analyse the first sensor data to determine a spatial location of the object. In this regard, the direction of the object is calculated relative to the current position and orientation of the user. Herein, information required to determine the direction of the object is obtained by analysing the first sensor data from different angles, triangulating a position of the object, using machine learning algorithms (for example, such as computer vision algorithms), and similar. Moreover, the determination of the direction of the object involves identifying whether the object is to a left direction, a right direction, a front direction, or other specific direction relative to the user. In this regard, the first sensor data includes distance and angle measurements.

[0049] Upon determining the direction of the object, the at least one processor is configured to send drive signals to the set of haptic actuators, wherein the drive signals are indicative of instructions to generate specific haptic feedback patterns by controlling the set of haptic actuators. Herein, the haptic feedback comprises vibrations or pulses that the user can feel on their skin. Moreover, the haptic feedback conveys information regarding presence of the object in the predefined FOV, and the direction of that object relative to the user. Moreover, different patterns or locations of the haptic feedback can convey different information. Moreover, the at least one processor is configured to control the set of haptic actuators to provide the haptic feedback indicating the distance between the object and the user. For example, a vibration on the left side produced by the at least one first side haptic actuator may indicate detection of the object in the left direction of the user, while a vibration in the centre produced by the at least one rear haptic actuator may indicate that an object is directly ahead.

[0050] A technical effect of controlling the set of haptic actuators in such a manner is that it allows the user to receive non-visual, intuitive cues about their surroundings within the predefined FOV. This ensures that the user can quickly and effectively respond to the object, which enhances their ability to navigate safely.

[0051] In an embodiment, when controlling the set of haptic actuators to provide the haptic feedback, the at least one processor is configured to perform at least one of: activate the at least one rear haptic actuator, when the object is detected to be present in the central zone, activate the at least one first side haptic actuator, when the object is detected to be present in the first side peripheral zone, activate the at least one second side haptic actuator, when the object is detected to be present in the second side peripheral zone.

[0052] In this regard, the at least one processor is configured to activate specific haptic actuators based on where the object has been detected within different zones relative to the user. The object may be detected to be present in a given zone when: at least 25 percent of a total size of the object is present in the given zone, or the object is present in at least a predefined percent of an FOV of the given zone, or similar. Such predefined percent could be set manually, or automatically. Moreover, such predefined percent is at the time of manufacturing the wearable device.

[0053] When the first set of obstacle sensors and the second set of obstacle sensors detect the object directly in front of the user, within the central zone, the at least one processor generates a drive signal to activate the at least one rear haptic actuator. Herein, the at least one rear haptic actuator provides the haptic feedback to indicate that the object is directly ahead. This enables the user to be immediately aware of objects directly in front of them, prompting them to take action to avoid a collision. When the first set of obstacle sensors and the second set of obstacle sensors detect the object on one side of the user, within the first side peripheral zone, the at least one processor generates another drive signal to activate the at least one first side haptic actuator. Herein, the at least one first side haptic actuator provides the haptic feedback to indicate that the object is present on that side of the user. This enables the user to understand a directional presence of the objects, and allows the user to adjust their movement accordingly to avoid the detected object on that side. This is useful for implementing shore-lining techniques. When the first set of obstacle sensors and the second set of obstacle sensors detect the object on another side of the user, within the second side peripheral zone, the at least one processor generates yet another drive signal to activate the at least one second side haptic actuator. Herein, the at least one side second haptic actuator provides the haptic feedback to indicate that the object is present on that other side of the user. This enables the user to understand a directional presence of the object, and allows the user to adjust their movement accordingly to avoid the detected object on that other side. This is useful for implementing shore-lining techniques. Moreover, when the object is present in 2 or more zones, the corresponding actuators of both zones will be activated.

[0054] A technical effect of the aforementioned is that it provides the user with clear and directional haptic feedback, thus improving their spatial awareness and navigation safety.

[0055] Optionally, the haptic feedback is indicative also of a distance between the object and the user, and wherein when controlling the set of haptic actuators to provide the haptic feedback, the at least one processor is configured to adjust an intensity of the haptic feedback according to the distance between the object and the user. In this regard, the at least one processor is configured to process the first sensor data to determine the distance between the user and the objects that were detected. Subsequently, the at least one processor is configured to dynamically adjust the intensity of the haptic feedback to correspond with the measured distance. Moreover, by adjusting the intensity of the haptic feedback based on the distance between the object and the user, the at least one processor of the wearable device can convey a sense of proximity or potential risk posed by the detected object. In an instance, when the objects are closer to the user, the intensity of the haptic feedback increases or is stronger. This alerts the user that potential hazards or obstacles are in immediate vicinity, which enables the user to take appropriate actions to avoid collisions or navigate safely. In another instance, when the objects move further away, the intensity of the haptic feedback decreases or is weaker. This alerts the user that potential hazards or obstacles are in their general surroundings, without causing unnecessary distractions. Optionally, the intensity of the haptic feedback is adjusted such that the intensity of the haptic feedback is inversely related to the distance between the object. Optionally, a manner in which the intensity of the haptic feedback is adjusted according to the distance between the object and the user, is tunable according to a preference of the user. In this regard, the user provides their preference via at least one input device and / or the user device.

[0056] A technical effect of the aforementioned is that it provides the user with a comprehensive and intuitive understanding of their surroundings, wherein a situational awareness of the user is enhanced. Furthermore, such haptic feedback enhances the user's ability to prioritize their attention and responses based on a perceived level of risk or proximity of the detected objects.

[0057] In an embodiment, the wearable device further comprises a first location sensor and at least one output device, wherein the at least one processor is further configured to: receive a first input pertaining to a navigation task, wherein the first input is indicative of at least a start location and a destination location of the navigation task; and at least while the user undertakes the navigation task, process second sensor data, collected by the first location sensor, to continuously track a location of the user; determine at least one navigation-assistance output that is to be provided to the user, based on the location of the user; and provide a navigation-assistance communication indicative of the at least one navigation-assistance output, via the at least one output device. Herein, the term "location sensor" refers to a device that is used to determine and provide a geographical position of the user. The first location sensor uses technologies to calculate coordinates (latitude, longitude, and altitude). Examples of the technologies may include, but are not limited to, Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), and Galileo. Such technologies are well- known in the art. Optionally, the first location sensor is a Global Positioning System Receiver. A technical effect of the aforementioned is that real-time guidance and / or route planning to the user is provided based on the geographical position of the user.

[0058] Herein, the term "output device" refers to a device that conveys information or feedback from the at least one processor to the user. The at least one output device provides auditory feedback. Hence, the at least one output device provides turn-by-turn instructions to the user to guide them. Optionally, the at least one output device comprises at least one speaker. The auditory feedback is provided using the at least one speaker. Examples of the auditory feedback may include, but are not limited to, a sound, an alarm, a spoken instruction. Optionally, the at least one output device provides another haptic feedback to navigate the user, by employing a haptic motor.

[0059] The first input comprises essential information required for initiating the navigation task, i.e., the start location and the destination location. Herein, the term "start location" refers to a location where the user begins their journey. The term "destination location" refers to a target location where the user intends to go. Herein, the start location and the destination location are any one of: entered manually via the interface, automatically detected by the first location sensor, selected from a list of predefined locations. The start location and the destination location can be provided in various formats, for example, such as GPS coordinates, addresses, landmarks, specific points of interest (POIs). Moreover, the first input can also include other information related to the navigation task, such as a date and time of undertaking the navigation task, a time period of completing the navigation task, a socio-ecological impact related to the navigation task, etc. Examples of socio-ecological impact: Least carbon footprint, Compliance with social distancing norms, etc.

[0060] The first input that pertains to the navigation task, involves guiding the user from the start location to the destination location. In this regard, the at least one processor can process the first input and plan instructions for navigation to guide the user. Hence, the navigation task comprises planning a route from the start location to the destination location, by considering various factors such as distance, terrain, and preferences of the user. Additionally, the navigation task could involve additional constraints or preferences, for example, such as avoiding specific areas, prioritizing pedestrian-friendly routes, and considering accessibility requirements.

[0061] The second sensor data that is collected by the first location sensor, includes latitude, longitude, altitude, optionally speed, direction, of the user. The at least one processor is configured to constantly update and monitor location of the user in real time or near-real time to ensure that the at least one processor has accurate and up-to-date position of the user. The term "navigation-assistance output" refers to guidance or alerts provided to the user that is determined based on both the location of the user and the presence of any objects detected in the predefined FOV. The at least one navigation-assistance output is communicated to the user via output devices, for example, such as haptic actuators, speakers, and similar. Examples of the at least one navigation-assistance outputs may include, but are not limited to, turn-by-turn directions, obstacle avoidance instructions, rerouting suggestions, and audio cues. For example, determine that the user needs to take a 90 degree right turn after walking straight for 100 metres, determine that the user needs to get off from a bus in which the user is traveling, after 5 stops, determine that the user needs to take the overhead walkway to cross a road, etc.

[0062] Subsequently, the at least one processor is configured to provide the navigation-assistance communication, which refers to actual messages or alerts provided to the user. The navigation-assistance communication effectively conveys necessary guidance to the user, even if they have visual impairments or if their vision is obstructed. In this regard, the navigation-assistance communication is provided regardless of detection of the object in the predefined FOV. The aforementioned steps can also be implemented prior to the user undertaking the navigation task. For example, the location of the user could be tracked even prior to the user undertaking the navigation task.

[0063] It will be appreciated that the wearable device is configured to detect the objects and carry out the navigation task independently, and has no influence or interaction with each other. In such instances, instructions provided by the navigation-assistance communication and the set of haptic actuators may conflict. As an exemplary scenario, a navigationassistance communication that is provided to the user may be to walk straight ahead even if an object may be present in front of the user. Such navigation-assistance communication may be provided as an audio instruction for example, "continue straight ahead" . Simultaneously, when it is detected that the object is present in the predefined FOV, the set of haptic actuators may alert the user to know that they cannot go straight ahead until they have avoided the object. Hence, the navigationassistance communication and the alert may conflict with each other.

[0064] A technical effect of the aforementioned is that it provides a comprehensive and adaptive navigation experience, thus ensuring user's successful completion of the navigation task. Optionally, the wearable device further comprises at least one input device comprising at least one of: a touch-based input device, a microphone. In this regard, the at least one input device allows the user to conveniently control the wearable device, as per the user's preference. Herein, the at least one input device is easy-to-use for the users that are visually-impaired. When the at least one input device is implemented as the touch-based input device, the "touch-based input device" refers to an interface that enables the user to interact with the wearable device by directly touching its surface. Examples of the touch-based input device may include, but are not limited to, a touch panel, buttons, sliders, rotatable knobs, braille touchpad, and similar. When the at least one input device is implemented as the microphone, the microphone enables voice recognition functionality. In other words, the user can provide voice commands to control the wearable device thereby enabling hands-free operation. Hence, the at least one input device allows basic control of the navigational software application without using the user device associated with the user, thus providing a hands-free experience.

[0065] Beneficially, the at least one of: the touch-based input devices, the microphone, accommodates the user with different abilities and accessibility needs. The touch-based input device caters to users who prefer tactile interaction, while the microphone benefits the user with mobility impairments, visual impairments, or conditions that limit manual dexterity. In some instances, the user can choose a preferred method of providing input that best suits the surrounding environment. For example, the user may opt for the touch-based input device in quiet environments and switch to the microphone in noisy or hands-busy situations. This adaptability ensures seamless interaction with the wearable device in diverse contexts.

[0066] Optionally, at least the first input pertaining to the navigation task is provided by the user via the at least one input device. In this regard, the at least one processor may optionally be further configured to execute a navigational software application, and employ the input for said execution, for enabling the user to undertake the navigation task. Alternatively, optionally, the first input is provided by the user via the user device that is communicably coupled to the wearable device. In this regard, a navigational software application may be executed at the user device. In this regard, functions for at least one of: pausing the navigation task, repeating the navigation task, changing a mode of transportation during the navigation task, a user preference with respect to the navigation task, shortcuts related to the navigation task, can be initiated in the navigational software application remotely by the at least one processor of the wearable device. Such functions are describes in detail below. As an example, in the navigational software application, the functions may be labelled in the following manner: a label for pausing the navigation task may be "pause", a label for repeating the navigation task may be "repeat", a label for changing a mode of transportation during the navigation task may be "bus mode" , an exemplary label for the user preference with respect to the navigation task may be "go to work", a shortcut label for a shortcut related to the navigation task may be "home". technical effect of incorporating at least one of: the touch-based input device and the microphone into the wearable device is that it enables enhancement of interaction modalities of the user, leading to a versatile and adaptable user interface.

[0067] Optionally, the at least one processor is further configured to: receive at least one of: a second input pertaining to selection of a visual impairment, a third input pertaining to selection of a mode of transportation during the navigation task, a fourth input pertaining to selection of an obstacle-sensing distance, a fifth input pertaining to occurrence of an emergency situation, a sixth input pertaining to a user preference with respect to the navigation task, a seventh input indicative of a spatial context of the navigation task, via at least one input device; process the at least one of: the second input, the third input, the fourth input, the fifth input, the sixth input, the seventh input, to implement a corresponding functionality in the wearable device.

[0068] In this regard, various types of inputs can be received by the at least one processor of the wearable device via the at least one input device, and the corresponding functionality is implemented based on the received input.

[0069] Herein, the "second input" refers to an input received by the at least one processor of the wearable device that pertains to selection of the visual impairment. In this regard, the second input is provided by the user initially through the user device associated with the user, by interacting with the navigational software application in the user device. The second input is saved in a memory of the user device, and is received by the at least one processor of the wearable device. The at least one processor is then configured to control the set of haptic actuators based on the second input.

[0070] Herein, the second input enables the user to specify their particular visual impairment (for example, such as macular degeneration, tunnel vision, peripheral vision loss, central vision loss, total blindness, and similar). Then, the at least one processor of the wearable device uses the second input to adjust its obstacle detection and the haptic feedback to better suit needs of the user based on their particular visual impairment by zoning the haptic actuators. It will be appreciated that by enabling the selection of the visual impairment, the wearable device can customize the haptic feedback and obstacle detection sensitivity.

[0071] As an example, in the second input, the user may specify the particular visual impairment to be macular degeneration which is impairment of the centre of FOV of the user. Upon receiving the second input, the at least one first side haptic actuator and the at least one second side haptic actuator may be turned off whilst the at least one rear haptic actuator remains on. As another example, in the second input, the user may specify the particular visual impairment to be tunnel vision which is impairment of peripherals of FOV of the user. Upon receiving the second input, the at least one rear haptic actuator is turned off while the at least one first side haptic actuator remains on. A further example includes where a user has an impairment on one side and wants feedback for their 'blind spot', wherein the relevant haptic actuator will be switched off depending on their preferences.

[0072] The "third input" refers to an input received by the at least one processor of the wearable device that pertains to the selection of the mode of transportation for the navigation task. The third input enables the user to specify their mode of transportation (for example, such as walking, using a wheelchair, and using public transportation, etc.). Then, the at least one processor of the wearable device processes the third input to provide navigation assistance that is optimized for the selected mode of transportation, for example, such as providing different types of cues or altering the obstacle detection range. It will be appreciated that by enabling the user to select their mode of transportation, the wearable device can adjust its obstacle detection range and haptic feedback intensity accordingly. This adaptability improves safety of the user and an accuracy of the wearable device across various transportation scenarios.

[0073] The "fourth input" refers to an input received by the at least one processor of the wearable device that pertains to the selection of an obstacle-sensing distance. The fourth input enables the user to specify the distance at which the wearable device should detect obstacles in a particular space. Then, the at least one processor of the wearable device uses the fourth input to adjust sensitivity and range of the first set of obstacle sensors and the second set of obstacle sensors, ensuring that the haptic feedback provided to the user is appropriate for their chosen detection distance. Hence, such obstacle-sensing distance is fully adjustable, for example, such as far to near while on the go. As an example, the fourth input may be 1 metre as the obstacle-sensing distance for an indoor space. As another example, the fourth input may be 3 metres as the obstacle-sensing distance for an outdoor space. It will be appreciated that enabling the user to set the obstacle-sensing distance based on their environment and comfort level helps to optimize performance of the wearable device. This flexibility reduces unnecessary alerts and enhances navigational confidence, adjusted to the immediate surroundings of the user.

[0074] The "fifth input" refers to an input received by the at least one processor of the wearable device that pertains to an occurrence of an emergency situation. In this regard, the fifth input is provided by the user via the user device that is communicably coupled to the wearable device, via an emergency-related software application. Herein, the emergency-related software application may be executed at the user device. Moreover, the fifth input is used to trigger emergency protocols (for example, such as sending the fifth input of Get me home functionality, feeling unsafe / unwell, wearable device failure / errors, or performing other emergency actions). It ensures that the user can quickly and effectively respond to unexpected dangerous situations, enhancing safety and security. It will be appreciated that the capability of the wearable device to recognize and respond to emergency situations through a dedicated input ensures rapid and appropriate action during crises. This feature significantly enhances safety of the user by providing immediate support and communication during critical moments.

[0075] The "sixth input" refers to an input received by the at least one processor of the wearable device that pertains to a user preference with respect to the navigation task. The sixth input enables the user to customize various aspects of the navigation assistance provided by the wearable device (for example, such as preferred routes, avoiding certain types of environments). Then, the at least one processor of the wearable device processes the sixth input to adjust the navigation outputs to align with personal preferences of the user. It will be appreciated that incorporating user preferences for the navigation task enables the wearable device to offer a more personalized and comfortable user experience. This personalization increases satisfaction of the user and encourages consistent use of the wearable device.

[0076] The "seventh input" refers to an input received by the at least one processor of the wearable device that is indicative of the spatial context of the navigation task. The seventh input provides information about the environment in which the user is navigating (for example, such as the navigation task in an indoor environment or an outdoor environment, the navigation task in an environment that the user has visited previously, and the like). Then, the at least one processor uses the seventh input to adjust its navigation assistance and obstacle detection strategies to suit the specific characteristics of the environment, improving the accuracy and relevance of the assistance provided. It will be appreciated that the ability of the wearable device to adapt to the spatial context of the navigation task ensures high performance and reliability. This adaptability provides consistent and dependable assistance regardless of environmental conditions.

[0077] Subsequently, the at least one processor is configured to generate the drive signals to control the set of haptic actuators to implement the corresponding functionality. Furthermore, optionally, the at least one of: the second input, the third input, the fourth input, the fifth input, the sixth input, the seventh input, is provided by the user via the at least one input device. A technical effect of aforesaid claim is that the wearable device becomes highly adaptable to the specific conditions and preferences provided by the user, thereby enhancing usability and effectiveness of the wearable device.

[0078] In an embodiment, when implementing the corresponding functionality, the at least one processor is configured to implement at least one of: adjust the haptic feedback, based on the visual impairment selected in the second input; selectively activate one or more obstacle sensors amongst the first set of obstacle sensors and the second set of obstacle sensors based on the visual impairment selected in the second input; select a type of navigation assistance in the at least one navigationassistance output, based on the mode of transportation selected in the third input; control the first set of obstacle sensors and the second set of obstacle sensors to collect the first sensor data up to the obstacle-sensing distance selected in the fourth input; perform at least one of: initiate execution of an emergency navigation task from a current location of the user to a pre-set safe location, send a communication indicative of the emergency situation to a user device of another user who is pre-selected by the user for receiving said communication, restart the wearable device in the emergency situation, based on the indication of the occurrence of the emergency situation in the fifth input; determine the at least one navigation-assistance output, based also on the user preference provided in the sixth input; set the obstacle-sensing distance, based on the spatial context provided in the seventh input; adjust an extent of the predefined FOV, based on the user preference provided in the sixth input and / or the spatial context provided in the seventh input.

[0079] In this regard, various specialized functionalities can be implemented corresponding to the various inputs mentioned above. A technical effect of the aforementioned is that diverse needs and preferences of the user are met by adjusting the haptic feedback, selectively activating the one or more obstacle sensors amongst the first set of obstacle sensors and the second set of obstacle sensors, tailoring navigation assistance, and responding to emergencies.

[0080] In the first instance, the at least one processor receives the second input, which specifies the type of visual impairment the user has. The at least one processor generates and sends the drive signals to adjust at least one of: the intensity, the frequency, the pattern, of the haptic feedback to suit the selected visual impairment. This is because different types of visual impairments might require different levels or types of feedback for effective navigation and object detection.

[0081] In a second instance, the at least one processor receives the third input, which indicates the user's mode of transportation. Herein, based on the mode of transportation selected, the processor can determine the appropriate type of navigation assistance to provide in the navigation assistance output. In this regard, different modes of transportation require different types of navigation instructions for safety and efficiency.

[0082] In a third instance, the at least one processor receives the fourth input specifying the obstacle-sensing distance. In this regard, the at least one processor is configured to collect the first sensor data up to the obstaclesensing distance, by adjusting the range within which the objects are detected. This allows the user to det a preferred sensing range to detect the objects, thus focusing on relevant areas of interest.

[0083] In a fourth instance, the at least one processor receives the fifth input indicating the occurrence of an emergency situation from the emergency- related software application. The at least one processor is configured to provide an emergency response to provide immediate assistance during emergencies, thus ensuring user safety and alerting designated contacts. In an instance, when an emergency navigation task is executed, the first location sensor determines the current location of the user in real time or near-real time. A safe location is pre-configured in the at least one processor, which could be a predefined address (for example, an address of a home of the user), a designated safe zone, a nearest help point. The at least one processor within the wearable device activates optionally a specialized navigation algorithm that is designed for emergency situations. In another instance, the user selects the user device of another user, wherein the another user is a trusted contact person. In this regard, information (for example, such as a phone number, an email address) pertaining to the another user is stored in a memory user device. When the at least one processor of the wearable device detects an emergency, the communication may be sent detailing the emergency situation. Herein, the communication could comprise at least one of: a nature of the emergency, a current location of the user. This communication is then sent from the wearable device to the user device of the other user using a communication method, for example, such as a message, an email, a notification on the emergency-related software application, and similar. In yet another instance, the at least one processor is optionally configured to determine that a restart is necessary to resolve an issue and restore normal functionality of the wearable device. This decision to restart the wearable device could be based on any predefined criteria or failure diagnostics. The wearable device is restarted to restore normal operations, so that the wearable device operates in a reliable manner when there is the indication of the occurrence of the emergency situation.

[0084] In a fifth instance, the at least one processor receives the sixth input detailing the user's preferences for assisting in navigation. These preferences are integrated into the at least one navigation-assistance output, to customize navigation instructions to match the user's preferences. Beneficially, it ensures that the least one navigationassistance output is in line with user's preferences. For example, the user may prefer routes with fewer stairs, or may prefer audio cues over haptic cues.

[0085] In a sixth instance, the at least one processor receives the seventh input that provides the spatial context, (for example, such as the indoor environment, the outdoor environment, crowded areas, open spaces). In this regard, the at least one processor dynamically adjusts the obstaclesensing distance of the first set of obstacle sensors and the second set of obstacle sensors. This feature ensures that the object is detected appropriately based on the spatial context, which enhances user safety and accuracy of navigating the user.

[0086] In a seventh instance, the extent of the predefined FOV is adjusted to match the user's preferences and the spatial context (i.e., an environmental context). Such provision provides a customized and effective user experience by dynamically adjusting the predefined FOV to meet specific needs and situational requirements of the user.

[0087] Optionally, the wearable device further comprising at least one orientation sensor, wherein the at least one processor is further configured to process third sensor data, collected by the at least one orientation sensor, to perform at least one of: determine an orientation of the user in an environment, improve an accuracy of motion-tracking data pertaining to urban environments. In this regard, the at least one orientation sensor detects and measures the orientation of the wearable device relative to its surroundings. The third sensor data provides essential information that is processed by the at least one processor to perform at least one of: determine the orientation of the user in an environment, improve the accuracy of the motion-tracking data particularly to urban environments, where GPS signals may be unreliable. Hence, the at least one orientation sensor augments a location functionality of the user device associated with the user. Examples of the at least one orientation sensor may include, but are not limited to, a magnetometer, an inertial measuring unit (IMU) (for example, such as an accelerometer and a gyroscope). Herein, the at least one processor employs processing algorithms to process the third sensor data to determine orientation of the user in their environment. This determination is facilitated by processing the third sensor data collected by the at least one orientation sensor, which may include measurements related to at least one of: a tilt, a rotation, a direction, of the wearable device relative to its surroundings. Thereby, upon analysing these measurements, the at least one processor can calculate the orientation of the wearable device and consequently the orientation of the user wearing the wearable device with respect to their surroundings. For example, the at least one orientation sensor may be a magnetometer. The magnetometer may improve an accuracy of determining which way the user is facing, particularly if they are stationary or if a signal received from a second location sensor may be weak.

[0088] Furthermore, in urban environments where Global Positioning System (GPS) signals received from the user device may be unreliable, motiontracking data can help to augment location information. The at least one orientation sensor collects data on the at least one of: an acceleration, a rotation, an orientation, of the user. However, when the GPS signals of the user device are weak, the at least one processor of the wearable device may use the motion-tracking data to estimate the current position of the user based on their last known GPS position. In other words, when the GPS signal of the user device may be weak, the navigational software application could be used to switch priority to the first set of obstacle sensors and the second set of obstacle sensors comprised in the wearable device. Thereby, analysing the direction and distance travelled, the at least one processor is configured to provide an estimated location. For example, at least one of: the at least one orientation sensor, the accelerometer, may be used to estimate distance travelled from last known position of the user, when the GPS signals received from the user device are weak.

[0089] A technical effect of using the at least one orientation sensor in such a manner is that there is enhanced accuracy in determining the orientation of the user, which improves navigation abilities of the wearable device.

[0090] Optionally, the wearable device further comprising at least one of: an accelerometer, a gyroscope, a compass, an orientation sensor, wherein the at least one processor is configured to: receive fourth sensor data, collected by the at least one of: the accelerometer, the gyroscope, the compass, the orientation sensor; determine whether an accuracy of fifth sensor data, collected by a sensor arrangement in a user device that is communicably coupled to the wearable device, is lesser than a second predefined threshold, wherein the sensor arrangement comprises at least one of: a second location sensor, a motion sensor; when it is determined that the accuracy of the fifth sensor data is lesser than the second predefined threshold, generate motion-tracking data comprising one of: the fourth sensor data, the fifth sensor data augmented with at least a portion of the fourth sensor data; and process the motion-tracking data to determine a pose of the user and / or motion information of the user.

[0091] In this regard, the "accelerometer" refers to a sensor that measures the acceleration forces acting on the wearable device. The acceleration forces can be due to gravity or a change in position of the wearable device itself. Herein, the accelerometer provides data on a rate of speed of the user, which is essential for accurate motion-tracking and navigation. The "gyroscope" refers to a sensor that measures a rate of rotation around three axes (such as a pitch, a roll, and a yaw) of the wearable device. Herein, the gyroscope offers precise information about rotational movements of the user, helping to determine changes in orientation and maintaining stability in motion tracking. The "compass" refers to a sensor that detects the Earth's magnetic field to determine the wearable device's direction relative to magnetic north. Herein, the compass is used to provide directional information, ensuring that the user can navigate accurately by understanding their orientation relative to the Earth's magnetic field. The "orientation sensor" refers to a sensor that determines orientation in three-dimensional space of the wearable device. Herein, the orientation sensor integrates data from various sources to provide a comprehensive understanding of spatial orientation of the user, which is essential for accurate pose determination and navigation assistance.

[0092] Herein, the at least one processor is configured to receive the fourth sensor data collected by the at least one of: the accelerometer, the gyroscope, the compass, the orientation sensor to enable a more accurate and comprehensive understanding of movements and orientation of the user. Moreover, the presence of multiple sensors offers redundancy and enhances accuracy of the wearable device. If one sensor fails or provides inaccurate data due to external factors such as magnetic interference for the compass sensor, the at least one processor can rely on data from other sensors to maintain functionality and ensure accurate tracking.

[0093] In this regard, the wearable device is communicably coupled to the user device (for example, such as a smartphone) which has its own sensor arrangement. Herein, the user uses the navigational software application to at least one of: access map data in real time or near-real time via Global System for Mobile Communications (GSM) or mobile internet data through a SIM card of the user device, provide an input related to the navigation task, plan routes based on the navigation task, track location using the second location sensor. This enables the user to successfully accomplish the navigation task.

[0094] It will be appreciated that the user device comprises another processor that is configured to collect the fifth sensor data. The at least one processor is further configured to assess whether the accuracy of the fifth sensor data is below the second predefined threshold. This determination is done by comparing the fourth sensor data and the fifth sensor data. Herein, greater the difference between the fourth sensor data and the fifth sensor data, lesser is the accuracy of the fifth sensor data. Hence, the at least one processor compensates for this by using the fourth sensor data. The term "second predefined threshold" refers to a predetermined range of values used to evaluate a reliability of the fifth sensor data. Such second predefined threshold may, for example, be set based on at least one of: a type of the wearable device, a type of the user device. Subsequently, the at least one processor is configured to generate the motion-tracking data, which can either be the fourth sensor data alone or the fifth sensor data augmented with the fourth sensor data. Hence, the orientation and details of the movement of the user is derived from processing the motion-tracking data.

[0095] Optionally, the pose of the user comprises at least one of: a position, an orientation, of the user. Optionally, the motion information comprises at least one of: a speed, a direction, a time duration, of motion of the user. Optionally, the at least one processor is configured to automatically determine a mode of transport being utilised by the user when undertaking the navigation task, based on the motion information.

[0096] Optionally, the wearable device further comprising a first wireless communication means that is communicably coupled to a second wireless communication means of a user device, wherein at least one of: the first input pertaining to the navigation task, a fifth sensor data collected by a sensor arrangement in the user device, is communicated from the second wireless communication means to the first wireless communication means.

[0097] In this regard, the term "wireless communication means" refers to protocols utilized by the wearable device and / or the user device to establish and maintain wireless communication with each other. Herein, the wireless communication means involves use of wireless communication protocols (such as Bluetooth®, Wi-Fi). Herein, upon establishing wireless connection between the wearable device and the user device, the first input related to the navigation task and / or the fifth sensor data collected by the sensor arrangement in the user device, can be transmitted from the user device to the wearable device. This communication enhances the functionality and effectiveness of the wearable device by providing access to real-time information collected by the user device. Beneficially, establishing the wireless communication means empowers the wearable device to provide accurate and up-to-date guidance during navigation tasks which enhances confidence and convenience of the user. Moreover, accessing the fifth sensor data from the user device enhances the accuracy and precision of operations of the wearable device, particularly in scenarios like indoor navigation where the GPS signals may be limited. A technical effect of establishing the wireless communication means between the user device and the wearable device is the improved synergy and data exchange capability. This enables seamless transmission of the at least one of: the first input pertaining to the navigation task, the fifth sensor data collected by the sensor arrangement in the user device, enhancing the ability of the wearable device to provide more accurate and contextually aware navigation assistance to the user.

[0098] Optionally, the wearable device further comprising a rechargeable battery arranged in the wearable device such that the rechargeable battery provides power to at least the first set of obstacle sensors, the second set of obstacle sensors, the set of haptic actuators, the first location sensor, the at least one output device, and the at least one processor.

[0099] In this regard, the term "rechargeable battery" refers to an energy storage device capable of storing electrical energy and subsequently releasing it as needed to constituents integrated within the wearable device. The rechargeable battery serves as a primary power supply for the wearable device, providing energy to operate at least one of: the first set of obstacle sensors, the second set of obstacle sensors, the set of haptic actuators, the first location sensors, the at least one output device, the at least one processor. Optionally, the rechargeable battery provides energy to at least one of: the at least one orientation sensor, the accelerometer, the gyroscope, the compass, the at least one input device. For example, the rechargeable battery could be a high-capacity Universal Serial Bus Type-C (USB-C) rechargeable on-board lithium battery integrated within the wearable device. The rechargeable battery is characterized by its large capacity hence allowing it to store a significant amount of the electrical energy. Beneficially, the rechargeable battery comprises a lithium composition, which ensures efficient energy storage and delivery. Furthermore, it contributes to extended usage times for the wearable device. This feature enhances portability and usability of the wearable device, enabling users to rely on said wearable device for prolonged periods without the need for frequent recharging. In this regard, by utilizing the rechargeable battery, the wearable device can operate autonomously for extended periods, offering continuous functionality to users without the need for frequent battery replacements. For example, the wearable device may operate continuously for at least four hours on a single charge of its rechargeable battery. Thus, a longer battery life is particularly advantageous for the wearable device intended for continuous use throughout the day, such as those supporting navigation or monitoring tasks.

[0100] A technical effect of including the rechargeable battery in the wearable device is the provision of a reliable and portable power source, enabling the wearable device to operate autonomously. This ensures continuous functionality of the wearable device, allowing the user to rely on it for extended periods without the need for frequent battery replacements or external power connections.

[0101] The present disclosure also relates to the second aspect as described above. Various embodiments and variants disclosed above, with respect to the aforementioned first aspect, apply mutatis mutandis to the second aspect.

[0102] DETAILED DESCRIPTION OF THE DRAWINGS

[0103] Referring to FIG. 1A, illustrated is a perspective view of a wearable device 100, and referring to FIG. IB, illustrated is a side view of a wearable device 100, in accordance with an embodiment of the present disclosure. With reference to FIG. 1A, the wearable device 100 comprises a first set 102A of obstacle sensors arranged in a first end portion 104 of the wearable device 100, a second set 102B of obstacle sensors arranged in a second end portion 106 of the wearable device 100, a set of haptic actuators, and at least one processor (not shown for sake of clarity). The at least one processor is communicably coupled with the first set 102A of obstacle sensors, the second set 102B of obstacle sensors, and the set of haptic actuators.

[0104] Herein, the first set 102A of obstacle sensors arranged in the first end portion 104 comprises at least one first Time-of-Flight (ToF) sensor (depicted as a first ToF sensor 108) and at least one first ultrasonic sensor (depicted as a first ultrasonic sensor 110), the second set 102B of obstacle sensors comprises at least one second ToF sensor (depicted as a second ToF sensor 112) and at least one second ultrasonic sensor (depicted as a second ultrasonic sensor 114), wherein the first set 102A of obstacle sensors and the second set 102B of obstacle sensors provide a predefined field of view (FOV) for object detection around the wearable device 100. Herein, the set of haptic actuators comprises at least one rear haptic actuator (depicted as a rear haptic actuator 116) arranged in a neckband 118 of the wearable device 100, at least one first side haptic actuator (depicted as a first side haptic actuator 120) arranged in the first side portion 122A of the wearable device 100 that lies between the neckband 118 and the first end portion 104, and at least one second side haptic actuator (depicted as a second side haptic actuator 124) arranged in the second side portion 122B of the wearable device 100 that lies between the neckband 118 and the second end portion 106.

[0105] Optionally, the wearable device 100 further comprises a first location sensor 126 and at least one output device (depicted as two output devices 128A and 128B). Optionally, the wearable device 100 further comprises at least one input device (depicted as two input devices 130A and 130B). Optionally, the wearable device 100 further comprises at least one orientation sensor (depicted as an orientation sensor 132). Optionally, the wearable device 100 further comprises a first wireless communication means 134 that is communicably coupled to a second wireless communication means of a user device. Optionally, the wearable device 100 further comprises a rechargeable battery 136 arranged in the wearable device 100 such that the rechargeable battery 136 provides power to at least the first set 102A of obstacle sensors, the second set 102B of obstacle sensors, the set of haptic actuators, and the at least one processor. The at least one processor is communicably coupled with the first location sensor 126, the output devices 128A-B, the input devices 130A-B, the orientation sensor 132, and the first wireless communication means 134.

[0106] With reference to FIG. IB, the side view of the wearable device 100 shows a right side view of the wearable device 100, wherein the first end portion 104 and the first side portion 122A are in view.

[0107] It may be understood by a person skilled in the art that the FIGs. 1A-1B includes a simplified perspective view and side view of the wearable device for sake of clarity, which should not unduly limit the scope of the claims herein. The person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0108] Referring to FIG. 2, illustrated is a predefined field of view (FOV) of a wearable device 100 provided by the first set 102A of obstacle sensors and the second set 102B of obstacle sensors of FIG. 1, in accordance with an embodiment of the present disclosure. With reference to FIG. 2, the predefined FOV comprises a first side peripheral zone 202 defined by an FOV 204 of at least one obstacle sensor in the first set of 102A obstacle sensors, a second side peripheral zone 206 defined by an FOV 208 of at least one obstacle sensor in the second set 102B of obstacle sensors, and a central zone 210 defined by a combined FOV 212 of one or more obstacle sensors in the first set 102A of obstacle sensors and one or more obstacle sensor in the second set 102B of obstacle sensors. It will be appreciated that the predefined FOV spans at least 180 degrees horizontal FOV. Herein, the first side peripheral zone 202 covers any one of a left side or a right side of a user. The first side peripheral zone 202 spans approximately 0.5 meters on the left side and extends to a distance of 1 meter from the user. Similarly, the second side peripheral zone 206 covers the right side of the user, extending from the central point in front of the user to the periphery on the right side. The second side peripheral zone 206 spans approximately 0.5 meters on the right and extends to a distance of 1 meter from the user. Herein, the central zone 210 covers the horizontal area directly in front of the user, extending from the user outward to a distance of 0.75 meters.

[0109] It may be understood by a person skilled in the art that the FIG. 2 includes a simplified predefined FOV and detection of zones of the wearable device 100 of FIG. 1 for sake of clarity, which should not unduly limit the scope of the claims herein. The person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0110] Referring to FIG. 3, illustrated is a graphical representation of performance of an ultrasonic sensor and a Time-of-Flight (ToF) sensor, in accordance with an embodiment of the present disclosure. With reference to FIG. 3, a vertical axis (Y-axis) represents performance levels. Herein, the performance levels comprise unaffected performance (labelled as 'Unaffected'), good performance (labelled as 'Good'), marginal performance (labelled as 'Marginal'), and poor performance (labelled as 'Poor') top to bottom of the Y-axis. The horizontal axis (X- axis) represents conditions and targets (depicted as CT that affect performance of the ultrasonic sensor and the ToF sensor. Herein, the conditions and targets CT are divided into two sections (namely, a left section and a right section) based on a strength of the ultrasonic sensor (as shown in the left section) and a strength of the ToF sensor (as shown in the right section). The various conditions and targets CT may include high ambient light levels (labelled as 'CT1'), transparent objects (labelled as 'CT2'), dark objects (labelled as 'CT3'), opaque curved objects (labelled as 'CT4'), uneven surfaces (labelled as 'CT5'), angled surfaces (labelled as 'CT6'), and soft objects (labelled as 'CT7').

[0111] As shown, when the conditions and targets comprise detecting the high ambient light levels CT1, ultrasonic sensors are not influenced by ambient light levels, making the ultrasonic sensors reliable in bright environments. Hence, the performance of the ultrasonic sensor is unaffected in conditions with the high ambient light levels CT1, while ToF sensors struggle in the high ambient light levels CT1 due to interference from light affecting measurement accuracy. Hence, the performance of ToF sensor is poor in the high ambient light levels CT1.

[0112] As shown, when the conditions and targets comprise detecting the transparent objects CT2, the ultrasonic sensor can detect the transparent objects effectively as the ultrasonic sensor rely on sound waves. Hence, the performance of the ultrasonic sensor is unaffected when detecting transparent objects CT2, while the ToF sensor have difficulty in detecting the transparent objects CT2 because light can pass through these objects, thereby leading to inaccurate distance measurements. Hence, the performance of the ToF sensor is marginal when detecting the transparent objects CT2.

[0113] As shown, when the conditions and targets comprise detecting the dark objects CT3, the ultrasonic sensor is effective in detecting the dark objects. Hence, the performance of the ultrasonic sensor is unaffected when detecting the dark objects CT3, while the ToF sensor can measure the time it takes for light to reflect back, making the ToF sensor reliable for detecting the dark objects CT3. Hence, the performance of the ToF sensor is good when detecting the dark objects CT3.

[0114] As shown, when the conditions and targets comprise detecting the opaque curved objects CT4, the ultrasonic sensor can detect the opaque curved objects well as the sound waves reflect back from the surface. Hence, the performance of the ultrasonic sensor is good when detecting the opaque curved objects CT4, while the ToF sensor handles curved objects effectively because the light reflects off the curves without significant loss of accuracy. Hence, the performance of the ToF sensor is unaffected when detecting the opaque curved objects CT4.

[0115] As shown, when the conditions and targets comprise detecting the uneven surfaces CT5, the ultrasonic sensor can scatter the sound waves, reducing the accuracy of the ultrasonic sensor. Hence, the performance of the ultrasonic sensor is marginal when detecting the uneven surfaces CT5, while the ToF sensor can accurately measure distances to the uneven surfaces CT5 as the ToF sensor analyzes time of flight of light, which is less affected by surface irregularities. Hence, the performance of the ToF sensor is unaffected when detecting the uneven surfaces CT5.

[0116] As shown, when the conditions and targets comprise detecting the angled surfaces CT6, the ultrasonic sensor can struggle as the sound waves may reflect away from the ultrasonic sensor, leading to inaccurate or missed detections. Hence, the performance of the ultrasonic sensor is marginal when detecting the angled surfaces CT6, while the ToF sensor is better at handling the angled surfaces CT6 as the light can reflect back accurately, allowing for precise distance measurements. Hence, the performance of the ToF sensor is unaffected when detecting the angled surfaces CT6.

[0117] As shown, when the conditions and targets comprise detecting the soft objects CT7, the ultrasonic sensor absorbs sound waves more than hard objects, which can reduce the detection range and accuracy of the ultrasonic sensor. Hence, the performance of the ultrasonic sensor is marginal when detecting the soft objects CT7, while the ToF sensor can detect the soft objects CT7 effectively because the reflection of light is less impacted by the softness of the material. Hence, the performance of the ToF sensor is good when detecting the soft objects CT7. It will be appreciated that understanding strengths and limitations of the ultrasonic sensor and the ToF sensor facilitates selection of the most suitable sensor for specific environmental conditions and detection requirements. Thereby combining both the ultrasonic sensor and the ToF sensor, a comprehensive object detection system can be achieved, capitalizing on the unique advantages offered by each sensor.

[0118] It may be understood by a person skilled in the art that the FIG. 3 includes a simplified graphical representation of performance of the ultrasonic sensor and the ToF sensor for sake of clarity, which should not unduly limit the scope of the claims herein. The person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0119] Referring to FIG. 4, illustrated are steps of a method implemented at the wearable device 100 of FIGs. 1A-B, in accordance with an embodiment of the present disclosure. At step 402, a first sensor data collected by a first set of obstacle sensors and a second set of obstacle sensors, is processed for detecting whether an object is present in a predefined FOV, wherein the predefined FOV is provided by the first set of obstacle sensors and the second set of obstacle sensors for object detection around the wearable device. At step 404, it is detected whether the object is present in the predefined FOV. When it is detected that the object is present in the predefined FOV, at step 406, a direction of the object with respect to a user is determined based on the first sensor data. Subsequently, at step 408, a set of haptic actuators are controlled to provide a haptic feedback indicative of at least the presence of the object in the predefined FOV and the direction of the object to the user. Alternatively, optionally when the object is not detected in the predefined FOV, at step 410, the first sensor data continues to be processed.

[0120] The aforementioned steps are only illustrative and other alternatives can also be provided where one or more steps are added, one or more steps are removed, or one or more steps are provided in a different sequence without departing from the scope of the claims herein.

Claims

CLAIMSWhat is claimed is:

1. A wearable device (100) that in use, is to be worn around a neck of a user, the wearable device comprising: a first set (102A) of obstacle sensors arranged in a first end portion (104) of the wearable device, wherein the first set of obstacle sensors comprises at least one first Time-of-Flight (ToF) sensor (108) and at least one first ultrasonic sensor (110); a second set (102B) of obstacle sensors arranged in a second end portion (106) of the wearable device, wherein the second set of obstacle sensors comprises at least one second ToF sensor (112) and at least one second ultrasonic sensor (114), and wherein the first set of obstacle sensors and the second set of obstacle sensors provide a predefined field of view (FOV) for object detection around the wearable device; a set of haptic actuators comprising at least one rear haptic actuator (116) arranged in a neckband (118) of the wearable device, at least one first side haptic actuator (120) arranged in a first side portion (122A) of the wearable device that lies between the neckband and the first end portion, and at least one second side haptic actuator (124) arranged in a second side portion (122B) of the wearable device that lies between the neckband and the second end portion; and at least one processor configured to: process first sensor data, collected by the first set of obstacle sensors and the second set of obstacle sensors, to detect whether an object is present in the predefined FOV; when it is detected that the object is present in the predefined FOV,determine a direction of the object with respect to the user, based on the first sensor data, and control the set of haptic actuators to provide a haptic feedback indicative of at least the presence of the object in the predefined FOV and the direction of the object, to the user.

2. A wearable device (100) according to claim 1, wherein the predefined FOV spans at least 180 degrees horizontal FOV.

3. A wearable device (100) according to claim 1 or 2, wherein the predefined FOV comprises: a first side peripheral zone (202) defined by an FOV (204) of at least one obstacle sensor in the first set (102A) of obstacle sensors, a second side peripheral zone (206) defined by an FOV (208) of at least one obstacle sensor in the second set (102B) of obstacle sensors, and a central zone (210) defined by a combined FOV (212) of one or more obstacle sensors in the first set of obstacle sensors and one or more obstacle sensors in the second set of obstacle sensors.

4. A wearable device (100) according to claim 3, wherein when controlling the set of haptic actuators to provide the haptic feedback, the at least one processor is configured to perform at least one of: activate the at least one rear haptic actuator (116), when the object is detected to be present in the central zone (210), activate the at least one first side haptic actuator (120), when the object is detected to be present in the first side peripheral zone (202), activate the at least one second side haptic actuator (124), when the object is detected to be present in the second side peripheral zone (206).

5. A wearable device (100) according to any of the preceding claims, wherein the haptic feedback is indicative also of a distance between the object and the user, and wherein when controlling the set of haptic actuators to provide the haptic feedback, the at least one processor is configured to adjust an intensity of the haptic feedback according to the distance between the object and the user.

6. A wearable device (100) according to any of the preceding claims, wherein when processing the first sensor data, the at least one processor is configured to: determine whether a level of confidence associated with a first portion of the first sensor data lies below a first predefined threshold, wherein the first portion of the first sensor data is collected by the at least one first ToF sensor (108) and the at least one second ToF sensor (112); when it is determined that the level of confidence associated with the first portion of the first sensor data lies below the first predefined threshold, prioritize utilization of a second portion of the first sensor data for detecting whether the object is present in the predefined FOV, wherein the second portion of the first sensor data is collected by the at least one first ultrasonic sensor (110) and the at least one second ultrasonic sensor (114); and when it is determined that the level of confidence associated with the first portion of the first sensor data is equal to or lies above the first predefined threshold, prioritize utilization of the first portion of the first sensor data for detecting whether the object is present in the predefined FOV.

7. A wearable device (100) according to claim 1, further comprising a first location sensor (126) and at least one output device (128A-B), wherein the at least one processor is further configured to:receive a first input pertaining to a navigation task, wherein the first input is indicative of at least a start location and a destination location of the navigation task; and at least while the user undertakes the navigation task, process second sensor data, collected by the first location sensor, to continuously track a location of the user; determine at least one navigation-assistance output that is to be provided to the user, based on the location of the user; and provide a navigation-assistance communication indicative of the at least one navigation-assistance output, via the at least one output device.

8. A wearable device (100) according to any of claim 1 or 7, wherein the at least one processor is further configured to: receive at least one of: a second input pertaining to selection of a visual impairment, a third input pertaining to selection of a mode of transportation during the navigation task, a fourth input pertaining to selection of an obstacle-sensing distance, a fifth input pertaining to occurrence of an emergency situation, a sixth input pertaining to a user preference with respect to the navigation task, a seventh input indicative of a spatial context of the navigation task, via at least one input device (128, 130); process the at least one of: the second input, the third input, the fourth input, the fifth input, the sixth input, the seventh input, to implement a corresponding functionality in the wearable device.

9. A wearable device (100) according to claim 8, wherein when implementing the corresponding functionality, the at least one processor is configured to implement at least one of:adjust the haptic feedback, based on the visual impairment selected in the second input; selectively activate one or more obstacle sensors amongst the first set (102A) of obstacle sensors and the second set (102B) of obstacle sensors based on the visual impairment selected in the second input; select a type of navigation assistance in the at least one navigationassistance output, based on the mode of transportation selected in the third input; control the first set of obstacle sensors and the second set of obstacle sensors to collect the first sensor data up to the obstacle-sensing distance selected in the fourth input; perform at least one of: initiate execution of an emergency navigation task from a current location of the user to a pre-set safe location, send a communication indicative of the emergency situation to a user device of another user who is pre-selected by the user for receiving said communication, restart the wearable device in the emergency situation, based on the indication of the occurrence of the emergency situation in the fifth input; determine the at least one navigation-assistance output, based also on the user preference provided in the sixth input; set the obstacle-sensing distance, based on the spatial context provided in the seventh input; adjust an extent of the predefined FOV, based on the user preference provided in the sixth input and / or the spatial context provided in the seventh input.

10. A wearable device (100) according to claim 7, further comprising at least one input device (130A-B) comprising at least one of: a touchbased input device, a microphone.

11. A wearable device (100) according to claims 7-10, further comprising at least one orientation sensor (132), wherein the at least one processor is further configured to process third sensor data, collected by the at least one orientation sensor, to perform at least one of: determine an orientation of the user in an environment, improve an accuracy of motion-tracking data pertaining to urban environments.

12. A wearable device (100) according to claim 7, further comprising at least one of: an accelerometer, a gyroscope, a compass, an orientation sensor, wherein the at least one processor is configured to: receive fourth sensor data, collected by the at least one of: the accelerometer, the gyroscope, the compass, the orientation sensor; determine whether an accuracy of fifth sensor data, collected by a sensor arrangement in a user device that is communicably coupled to the wearable device, is lesser than a second predefined threshold, wherein the sensor arrangement comprises at least one of: a second location sensor, a motion sensor; when it is determined that the accuracy of the fifth sensor data is lesser than the second predefined threshold, generate motion-tracking data comprising one of: the fourth sensor data, the fifth sensor data augmented with at least a portion of the fourth sensor data; and process the motion-tracking data to determine a pose of the user and / or motion information of the user.

13. A wearable device (100) according to any of claim 7 or 12, further comprising a first wireless communication means (134) that is communicably coupled to a second wireless communication means of a user device, wherein at least one of: the first input pertaining to the navigation task, a fifth sensor data collected by a sensor arrangement inthe user device, is communicated from the second wireless communication means to the first wireless communication means.

14. A wearable device (100) according to any of the preceding claims, further comprising a rechargeable battery (136) arranged in the wearable device such that the rechargeable battery provides power to at least the first set (102A) of obstacle sensors, the second set (102B) of obstacle sensors, the set of haptic actuators, and the at least one processor.

15. A method implemented at the wearable device (100) of any of the preceding claims, the method comprising: processing first sensor data, collected by the first set (102A) of obstacle sensors and the second set (102B) of obstacle sensors, for detecting whether an object is present in a predefined FOV, wherein the predefined FOV is provided, by the first set of obstacle sensors and the second set of obstacle sensors, for object detection around the wearable device; when it is detected that the object is present in the predefined FOV, determining a direction of the object with respect to the user, based on the first sensor data, and controlling the set of haptic actuators to provide a haptic feedback indicative of at least the presence of the object in the predefined FOV and the direction of the object, to the user.

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