Smart wearable system for team performance assessment and score generation

Abstract

A smart wearable system (200) for assessing team performance and determining a team performance score is disclosed The system comprises an apparel (104) integrated with a sensor unit (106) configured to capture performance-related data of players (102) during a sporting activity, a wireless communication module (206) for transmitting the data to a server (110) via a communication network (106). The server (110) comprises a processing unit (208) including modules for aggregating and temporally aligning the data, extracting features, normalizing features with respect to role-specific baselines, computing individual performance scores, computing coordination metrics, and generating a team performance score using a weighted combination of the individual performance scores and coordination metrics. A memory (210) stores role-specific baselines, historical logs, weight factors, and computed scores. A user device (112) presents the scores and reports to a user such as a coach or analyst.

Description

[0001] SMART WEARABLE SYSTEM FOR TEAM PERFORMANCE ASSESSMENT AND SCORE GENERATION

[0002] FIELD OF INVENTION

[0003] [1] The present invention generally relates to the field of smart wearable devices. More specifically, the present invention relates to a smart apparel-based system for assessing team performance and determining team performance score.

[0004] BACKGROUND OF THE INVENTION

[0005] [2] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.

[0006] [3] Wearable technologies have seen widespread use in sports and athletic training, primarily for monitoring physiological and motion-related parameters of individual players. Commonly available systems employ devices such as wristbands, chest straps, or apparel with integrated sensors to record metrics including heart rate, body temperature, acceleration, deceleration, distance covered, and positional coordinates using GPS or inertial measurement units. The information gathered is typically processed to generate performance statistics for a single player, such as workload, training intensity, fatigue levels, or recovery indices.

[0007] [4] In addition to physiological monitoring, player tracking technologies are used in various team sports to record spatial movement and coverage. Systems based on GPS, radio frequency, or camera-based vision tracking provide positional data and distance metrics for players during practice or competition. These solutions, however, are primarily limited to presenting individual positional information or raw statistical outputs, without integration into a broader framework for evaluating collective team activity.

[0008] [5] Despite these advances, existing wearable and tracking systems remain constrained in scope, as they are largely focused on outcome-oriented statistics or fragmented individual data streams. Current technologies do not adequately represent aspects such as role-specific execution, positional adherence, synchronization, or balance of effort across players. As a result, available solutions provide only a partial picture of performance and are insufficient for delivering a comprehensive evaluation of team dynamics.

[0009] [6] Thus, there remains a need of a smart apparel-based system for assessing team performance and determining team performance score to overcome the above-mentioned challenges.

[0010] OBJECTS OF THE INVENTION

[0011] [7] A general objective of the invention is to a smart apparel-based system capable of capturing physiological, motion, and positional data from multiple players simultaneously through apparel-integrated sensors.

[0012] [8] Another object of the present invention is to provide a system that enables wireless transmission of captured data of a plurality of players to a processing unit in real time or near real time.

[0013] [9] Yet another object of the present invention is to provide a processing framework configured to aggregate and temporally synchronize multi-player data streams for accurate comparative analysis.

[0014]

[0010] Yet another object of the present invention is to provide computation of individual performance scores for each player and team coordination metrics including formation stability, synchronization, and effort balance.

[0015]

[0011] Yet another object of the present invention is to provide a system adaptable to different sports by allowing customization of role-specific baselines and weighting factors.

[0016]

[0012] Yet another object of the present invention is to present invention to enable storage of performance data for longitudinal analysis and tracking of trends over time.

[0017]

[0013] Yet another object of the present invention is to provide injury prediction functionality by detecting abnormal muscle activation patterns, physiological anomalies, or workload imbalances that may indicate elevated injury risk.

[0018] SUMMARY OF THE INVENTION

[0014] This summary is provided to introduce aspects related to the present invention of a smart apparel-based system for assessing team performance and determining team score and the aspects are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.

[0019]

[0015] In an embodiment of the present disclosure, a smart wearable system is disclosed. The smart wearable system comprises a plurality of sensors integrated into an apparel and configured to capture performance-related data of a plurality of players during a sporting activity. The smart wearable system further comprises a wireless communication module communicatively coupled to the apparel. The wireless communication module is configured to transmit captured performance-related data to a server. The smart wearable system further comprises a processing unit within the server communicatively coupled to the wireless communication module. The processing unit is configured to aggregate and temporally align the captured performance-related data received from the wireless communication module. The processing unit is further configured to extract a set of features from aligned performance - related data. The processing unit is further configured to normalize extracted features with respect to role-specific baselines associated with the plurality of players. The processing unit is further configured to compute an individual performance score for each player based on normalized features. The processing unit is further configured to compute one or more coordination metrics among the plurality of players. The processing unit is further configured to generate a team performance score based on a weighted combination of the individual performance scores and the one or more coordination metrics.

[0020]

[0016] In an aspect of the present disclosure, the plurality of sensors comprises at least one of an electrocardiogram sensor (ECG), electromyography (EMG) sensor, an inertial measurement unit, a positioning sensor, a pressure sensor, a temperature sensor, a hydration sensor, or a respiration sensor.

[0021]

[0017] In another aspect of the present disclosure, the performance-related data comprises at least one of physiological data, motion data, or positional data.

[0022]

[0018] In another aspect of the present disclosure, the plurality of sensors is further configured to perform pre-processing of the captured performance-related data, wherein the pre-processing comprises at least one of noise filtering, timestamping of the data, and buffering of data packets.

[0023]

[0019] In another aspect of the present disclosure, the wireless communication module is configured to operate using at least one of Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), Ultra-Wideband (UWB) and radio frequency (RF).

[0024]

[0020] In another aspect of the present disclosure, the set of features comprises at least one of physiological features, motion features, and positional features.

[0025]

[0021] In another aspect of the present disclosure, the one or more coordination metrics comprises at least one of formation stability, synchronization, relative benchmarking, balance of effort distribution, or inter-player coupling.

[0026]

[0022] In another aspect of the present disclosure, the server further comprises a memory communicatively coupled with the processing unit. The memory is configured to store program instructions executable by the processing unit, the performance-related data, the role-specific baselines, historical trend and log data, weight factors for score computation, the individual performance score and team performance score.

[0027]

[0023] In another aspect of the present disclosure, the weights are configurable based on a type of sport.

[0028]

[0024] In another aspect of the present disclosure, the smart wearable system further comprises a user device to display the team performance score, generate post-session reports including a timeline of the team performance score, individual performance scores, and component breakdowns.

[0029]

[0025] In another aspect of the present disclosure, the user device is selected from the group comprising of a mobile phone, a tablet, a computer, a smartwatch, or a web -based dashboard.

[0030]

[0026] In another aspect of the present disclosure, the processor further configured to provide injury prediction and workload management of the players.

[0027] In another aspect of the present disclosure, the apparel further comprises a battery configured to supply power to the plurality of sensors and the controller.

[0031]

[0028] In another embodiment of the present disclosure, a method for generating a team performance score is disclosed. The method comprises capturing performance-related data of a plurality of players during a sporting activity via a plurality of sensors. The method further comprises transmitting captured performance-related data to a server via a wireless communication module. The method further comprises aggregating and aligning the performance-related data received from the wireless communication module by a processing unit. The method further comprises extracting a set of features from aligned performance- related data by the processing unit. The method further comprises normalizing extracted features with respect to role-specific baselines associated with the plurality of players by the processing unit. The method further comprises computing an individual performance score for each player based on normalized features by the processing unit. The method further comprises computing one or more coordination metrics among the plurality of players by the processing unit. The method further comprises generating a team performance score based on a weighted combination of the individual performance scores and the one or more coordination metrics by the processing unit.

[0032]

[0029] In an aspect of the present disclosure, the plurality of sensors comprises at least one of an ECG sensor, EMG sensor an inertial measurement unit, a positioning sensor, a pressure sensor, a temperature sensor, a hydration sensor, or a respiration sensor.

[0033]

[0030] In another aspect of the present disclosure, the performance-related data comprises at least one of physiological data, motion data, or positional data.

[0034]

[0031] In another aspect of the present disclosure, the plurality of sensors is further configured to perform pre-processing of the captured performance-related data, wherein the pre-processing comprises at least one of noise filtering, timestamping of the data, and buffering of data packets.

[0035]

[0032] In another aspect of the present disclosure, the wireless communication module is configured to operate using at least one of Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), Ultra-Wideband (UWB) and radio frequency (RF).

[0033] In another aspect of the present disclosure, the set of features comprises at least one of physiological features, motion features, and positional features.

[0036]

[0034] In another aspect of the present disclosure, the one or more coordination metrics comprises at least one of formation stability, synchronization, balance of effort distribution, or inter-player coupling.

[0037]

[0035] In another aspect of the present disclosure, the server further comprises a memory communicatively coupled with the processing unit. The memory is configured to store program instructions executable by the processing unit, the performance -related data, the role-specific baselines, historical trend and log data, weight factors for score computation, the individual performance score and team performance score.

[0038]

[0036] In another aspect of the present disclosure, the weights are configurable based on a type of sport.

[0039]

[0037] In another aspect of the present disclosure, the smart wearable system further comprises a user device to display the team performance score, generate post-session reports including a timeline of the team performance score, individual performance scores, and component breakdowns.

[0040]

[0038] In another aspect of the present disclosure, the user device is selected from the group comprising of a mobile phone, a tablet, a computer, a smartwatch, or a web-based dashboard.

[0041]

[0039] In another aspect of the present disclosure, the processor further configured to provide injury prediction and workload management of the players.

[0042]

[0040] In another aspect of the present disclosure, the apparel further comprises a battery configured to supply power to the plurality of sensors and the controller.

[0043] BRIEF DESCRIPTION OF THE DRAWINGS

[0044]

[0041] The accompanying drawings constitute a part of the description and are used to provide further understanding of the present invention. Such accompanying drawings illustrate the embodiments of the present invention, which are used to describe the principles of the present invention. The embodiments are illustrated by way of example and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. It should be noted that references to “an” or “one” embodiment in this invention are not necessarily to the same embodiment, and they mean at least one. In the drawings:

[0045]

[0042] Fig. 1 illustrates a working environment of a smart wearable system for assessing team performance and determining team performance score, in accordance with an embodiment of the present invention.

[0046]

[0043] Fig. 2 illustrates block diagram of the smart wearable system for assessing the team performance and determining the team performance score, in accordance with an embodiment of the present invention.

[0047]

[0044] Fig. 3 illustrates block diagram of the processing unit depicting various functional modules, in accordance with an embodiment of the present invention.

[0048]

[0045] Fig. 4 illustrates a flowchart depicting a method for assessing team performance and determining the team performance score, in accordance with an embodiment of the present invention.

[0049]

[0046] A more complete understanding of the present invention and its embodiments thereof may be acquired by referring to the following description and the accompanying drawings.

[0050] DETAILED DESCRIPTION OF THE INVENTION

[0051]

[0047] Exemplary embodiments now will be described with reference to the accompanying drawings. The disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey its scope to those skilled in the art. The terminology used in the detailed description of the particular exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting. In the drawings, like numbers refer to like elements.

[0052]

[0048] It is to be noted, however, that the reference numerals used herein illustrate only typical embodiments of the present subject matter, and are therefore, not to be considered for limiting its scope, for the subject matter may admit to other equally effective embodiments.

[0049] The specification may refer to “an”, “another”, “one” or “some” embodiment s) in several locations.

[0053]

[0050] This does not necessarily imply that each such reference is to the same embodiment(s), or that the feature only applies to a single embodiment. Single features of different embodiments may also be combined to provide other embodiments.

[0054]

[0051] As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless expressly stated otherwise. It will be further understood that the terms “include”, “comprises”, “including” and / or “comprising” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It will be understood that when an element is referred to as being “connected” or “coupled” to another element, it can be directly connected or coupled to the other element or intervening elements may be present. Furthermore, “connected” or “coupled” as used herein may include operatively connected or coupled. As used herein, the term “and / or” includes any and all combinations and arrangements of one or more of the associated listed items.

[0055]

[0052] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0056]

[0053] The detailed description includes specific details for the purpose of providing a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without these specific details.

[0057]

[0054] The present invention discloses a smart wearable system for assessing team performance and determining a team performance score. Existing performance monitoring solutions are primarily focused on individual statistics and fail to capture the collective dynamics that define effective teamwork. Moreover, current systems often lack role-specific normalization, resulting in biased evaluations across players occupying different positions, and provide limited integration of coordination metrics that reflect real-time cooperation among players. The smart wearable system of the present invention overcomes these shortcomings by integrating multiple sensors within an apparel to capture physiological, motion, and positional data from multiple players, transmitting the data to a server for advanced processing, and employing dedicated modules for feature extraction, normalization, and computation of both individual and coordination metrics. By combining these inputs into a configurable weighted framework, the system generates a team performance score that provides a fair, comprehensive, and actionable measure of overall team performance.

[0058]

[0055] Fig. 1 illustrates a working environment of a smart wearable system (The smart wearable system is further described in details in Fig. 2) for assessing team performance and determining team performance score, in accordance with an embodiment of the present invention. As depicted in Fig. 1, a plurality of players 102-1, 102-2, ... 102-n, (hereinafter, for ease of explanation collectively referred to as players 102), are shown wearing apparels 104-1, 104-2, ...104-n (hereinafter, for ease of explanation collectively referred to as apparel 104) integrated with a plurality of sensors 106. The plurality of sensors 106 embedded within the apparel 104 are configured to capture performance-related data of the players 102 during a sporting activity.

[0059]

[0056] The captured performance-related data is communicated through a wireless communication module, where the wireless communication module establishes connectivity over a communication network 108. The communication network 108 may include, but is not limited to, Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), radio frequency (RF), Ultra-Wideband (UWB), or a combination thereof, and may be implemented in a direct transmission mode or in a mesh network topology. The wireless communication module thereby enables seamless and continuous transmission of the performance-related data from the players 102 to a server 110 for further processing and analysis.

[0060]

[0057] The server 110 comprises a processing unit that receives the performance-related data transmitted from the wireless communication module. The server 110 is configured to perform computational operations on received performance related data, which includes aggregating the performance related data from multiple players 104, temporally aligning the performance related data to a common reference, and subsequently extracting features relevant for performance analysis. Based on such extracted features and role-specific baselines, the server 108 determines an individual performance score for each player 102, computes coordination metrics that reflect the degree of synchronization and cooperation among the players 102, and further generates a team performance score by applying a weighted combination of the individual performance scores and the coordination metrics.

[0061]

[0058] The generated team performance score, along with corresponding individual performance scores and related breakdowns, is communicated from the server 110 to a user device 112. The user device 112 may be, for example, a mobile phone, a tablet, a computer, a smartwatch, or a web-based dashboard. The user device 112 provides an interface to a user 114 for viewing the real-time team performance score during the sporting activity or for accessing post-session reports including timelines, historical comparisons, and component-level analytics. The user 114 may include, but not limited to players 102, a coach, trainer, or an analyst, for viewing the real-time team performance score during the sporting activity or for accessing post-session reports including timelines, historical comparisons, and componentlevel analytics. The overall working environment therefore illustrates interaction between the players 102 equipped with the apparel 104, the communication network 108, the server 110, and the user device 112, which collectively enable the assessment of team performance and the generation of a team performance score.

[0062]

[0059] Fig. 2 illustrates a block diagram of the smart wearable system 200 for assessing team performance and determining team performance score, in accordance with an embodiment of the present invention. The smart wearable system 200 comprises the plurality of sensors 106 integrated with the apparel 104 of each player 102. The plurality of sensors 106 are hereinafter, for ease of explanation collectively referred to as a sensor unit 106. The sensor unit 106 is configured to capture performance-related data of the corresponding player 102 during a sporting activity.

[0063]

[0060] In one embodiment, the sensor unit 106 may include physiological sensors such as an electrocardiogram (ECG) sensor and heart-rate / heart-rate- variability sensing elements, motion sensing components such as an inertial measurement unit comprising an accelerometer and a gyroscope, positional sensing elements such as a global positioning system or ultra- wideband positioning module, pressure or force sensors for detection of foot-strikes and impacts, and optional environmental or physiological auxiliaries such as a temperature sensor, a hydration sensor and a respiration sensor. In another embodiment, the sensor unit 106 may also comprise electromyography (EMG) sensors configured to capture electrical activity associated with muscle contractions. The EMG sensors enable monitoring of muscular effort and coordination during gameplay and are capable of generating a muscle activation map across body regions of the players 102 by aggregating localized muscle activity data. The muscle activation map provides insights into workload distribution and supports advanced applications such as injury prediction and workload management for players 102. By identifying abnormal or imbalanced activation patterns, the EMG-based data may enable the system to provide early warning of potential injury risks and assist in optimizing training loads.

[0064]

[0061] The sensor unit 106 may be physically integrated into the apparel 104 by means of printed circuit assemblies, sewn pockets, conductive fabric traces, flexible printed electronics, snap-fit sensor housings or other suitable integration techniques to ensure stable mechanical coupling with the body of the player 102 and reliable acquisition of signals during dynamic movement.

[0065]

[0062] In one embodiment, the apparel 104 may further include a controller 202, communicatively coupled to the sensor unit 106. The controller 202 is configured to manage sensor sampling rates and schedules, to configure and control analog front-end circuitry, and to perform preprocessing of the captured performance-related data. The preprocessing performed by the controller 202 may include one or more of noise filtering to remove sensor and motion artifacts, digital filtering and signal conditioning, timestamping of sampled data using a local clock or synchronization tokens, event detection (for example, jump detection or impact detection) to identify and mark salient events, local aggregation of sensor samples into packets, rudimentary feature extraction for low-bandwidth reporting, and buffering of data packets to survive transient communication outages.

[0066]

[0063] The apparel 104 may further include a battery 204 configured to supply power to the sensor unit 106 and the controller 202. The battery 204 may be implemented as a rechargeable energy source such as a lithium-ion or lithium-polymer cell, and may further include a battery management system for cell protection, charging control, state-of-charge estimation and thermal monitoring.

[0067]

[0064] The smart wearable system 200 further include a wireless communication module 206 communicatively coupled to the apparel 104 and configured to transmit the captured performance-related data to the server 110 via the communication network 108. (as shown in Fig. 1). The wireless communication module 206 supports one or more wireless protocols and frequency bands including, but not limited to, Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), radio frequency (RF) links and Ultra-Wideband (UWB). In one embodiment, the wireless communication module 206 may operates in a direct transmission mode to communicate with a gateway or base station connected to the server 110. The server 110 may be implemented as a local edge server or as a remote cloud server accessible over internet. In another embodiment, the wireless communication module 206 is configured to operate in a mesh network topology, where multiple apparels 104 communicate with each other and at least one apparel 104 acts as a gateway node for relaying the performance-related data to the server 110.

[0068]

[0065] The smart wearable system 200 further include the server 110. The server 110 comprises a processing unit 208 that is communicatively coupled to the wireless communication module 206. The processing unit 208 may include various functional modules that are configured to execute multiple analytical and computational functions on the performance-related data transmitted from the apparel 104 (as illustrated in Fig. 3).

[0069]

[0066] The server 110 further comprises a memory 210 communicatively coupled to the processing unit 208. The memory 210 is configured to store program instructions executable by the processing unit 208, the raw and processed performance-related data, role-specific baselines, historical trend data and logs, configurable weight factors, as well as the computed individual performance scores and the team performance score. The memory 210 thereby enables both real-time processing and long-term analytics, such as monitoring player development over multiple sessions, comparing team performance across matches, and generating detailed reports for performance improvement.

[0070]

[0067] The processor 208 may include one or more general purpose processors (e.g., INTEL® or Advanced Micro Devices® (AMD) microprocessors) and / or one or more special purpose processors (e.g., digital signal processors or Xilinx® System on Chip (SOC) Field Programmable Gate Array (FPGA) processor), MIPS / ARM-class processor, a microprocessor, a digital signal processor, an application specific integrated circuit, a microcontroller, a state machine, or any type of programmable logic array.

[0071]

[0068] The memory 210 may include, but is not limited to, non-transitory machine- readable storage devices such as hard drives, magnetic tape, floppy diskettes, optical disks, Compact Disc Read-Only Memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, Random Access Memories (RAMs), Programmable Read-Only Memories (PROMs), Erasable PROMs (EPROMs), Electrically Erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media / machine- readable medium suitable for storing electronic instructions.

[0072]

[0069] The processing unit 208 may include a data aggregation and synchronization module 302 configured to receive and align the performance-related data streams originating from the players 102. The aggregation and synchronization module 302 perform temporal alignment of the incoming performance-related data using timestamps or synchronization references to ensure that the performance- related data from all players 102 corresponds to the same time window. This alignment is essential for accurate comparison and correlation of player activities, thereby enabling the system to interpret how individual actions contribute to team dynamics in real time or over the course of the session.

[0073]

[0070] The processing unit 208 further comprises a feature extraction module 304 configured to analyze temporally aligned data and extract a set of features relevant to performance assessment. The set of features may comprise at least one of physiological features, motion features, and positional features. The physiological features may include, without limitation, parameters such as heart rate, heart rate variability, respiration rate, body temperature, or hydration level. The motion features may include, without limitation, parameters such as distance covered, running speed, acceleration events, deceleration events, jump count, jump height, or impact load. The positional features may include, without limitation, player field coordinates, relative positioning with respect to teammates, formation spread, or zone adherence. The feature extraction module 304 thereby transforms raw sensor data into structured performance parameters that form the basis for subsequent scoring computations.

[0074]

[0071] The processing unit 208 further comprises a normalization module 306 configured to adjust extracted features with respect to role-specific baselines associated with the players 102. In one embodiment, the role-specific baselines may be predefined according to the playing position or role of each player 102, such as defender, midfielder, or forward in a team sport. In another embodiment, the baselines may be dynamically adapted during the course of play based on real-time measurements and observed trends. In yet another embodiment, the baselines may be derived from historical performance records maintained in the memory 210, thereby enabling personalized reference values for each player. The normalization module 306 ensures that the system accounts for natural differences in physiological capability and positional responsibility, thereby providing a fair and objective basis for comparing players occupying different roles within the team.

[0075]

[0072] The processing unit 208 further comprises an individual performance scoring module 308 configured to generate an individual performance score for each player 102 based on normalized features. The individual performance scoring module 308 assigns a quantified value that reflects the contribution and effort of each player during the sporting activity. In one embodiment, the score may be continuously updated during play to provide real-time feedback, or may be aggregated at the end of the session to provide an overall assessment of individual contribution.

[0076]

[0073] The processing unit 208 further include a coordination metrics computation module 310 configured to compute one or more coordination metrics among the players 102. The one or more coordination metrics may include formation stability, synchronization, balance of effort distribution, and inter-player coupling. The coordination metrics computation module 310 computes formation stability by analyzing positional features to determine zone adherence of individual player 102, deviations of individual player positions from assigned positions or from a team centroid over one or more-time windows, and by converting such deviations into a normalized stability score. The synchronization is computed by analyzing temporally aligned motion features to determine temporal correlation or phase-coherence of activity bursts (for example acceleration or deceleration events) across two or more players, and by mapping the degree of temporal alignment to a synchronization score.

[0077]

[0074] The balance of effort distribution is computed by deriving workload indices for each player 102 from normalized physiological and motion features, computing a statistical dispersion measure across the team, and translating the dispersion into a balance score that reflects evenness of effort. The inter-player coupling is computed by evaluating pairwise or subgroup similarity of movement trajectories or feature vectors and by aggregating pairwise coupling measures into a team-level coupling metric.

[0078]

[0075] The processing unit 208 further include a team performance scoring module 312 configured to generate a team performance score by combining the individual performance scores and the one or more coordination metrics. In one embodiment, the team performance scoring module 312 computes the team performance score using a weighted combination of the inputs, where the weights are configurable based on the type of sport being played. The weights may be defined by a coach, analyst, or system administrator, or selected from predefined templates corresponding to different sporting activities. This configurability enables the smart wearable system 200 to adapt its scoring methodology to reflect the specific dynamics and performance indicators most relevant to a given sport.

[0079]

[0076] The computation of the team performance score may be expressed by the following equation:

[0080] TPS =W i • A vg (IPS i)+W 2 - Formations tability+W 3 • S ynchronization+W 4 • B alance where TPS represents the team performance score, IPSi ... ZPSnrepresent the individual performance scores of the players 102, and Formation Stability, Synchronization, and Balance represent coordination metrics computed by the coordination metrics computation module 310. Wi, W2, Wi, and W4 are the weights that may be adjusted or configured depending on the sport. In one embodiment, the set of coordination metrics may further include inter-player coupling, which can be incorporated into the weighted combination with an associated weight.

[0081]

[0077] The team performance scoring module 312 is further configured to generate the team performance score either in real time, to support in-game feedback, or as an aggregated value at the conclusion of a session, to support post-session reporting and analysis.

[0082]

[0078] The smart wearable system 200 further include the user device 112. The user device 112 is configured to receive and display the team performance score generated by the team performance scoring module 312, together with the individual performance scores and the coordination metrics computed by the processing unit 208. In one embodiment, the user device 112 may further be configured to generate post-session reports including a timeline of the team performance score, trend graphs of individual player contributions, and detailed breakdowns of component features and coordination metrics. The user device 112 may be implemented as a mobile phone, tablet, computer, smartwatch, or a web-based dashboard, thereby enabling convenient access to performance data in real time during the sporting activity or in offline review sessions. In one embodiment, the user device 112 may further allow configuration of weight factors and role-specific baselines, thereby enabling a coach or analyst to tailor the scoring framework to the specific sporting context.

[0083]

[0079] A user 114, such as a coach, trainer, analyst, player himself or another authorized individual, interacts with the user device 112 to monitor and evaluate team performance. The user 114 may access the displayed team performance score and individual performance scores in real time to obtain immediate insights during the sporting activity, or may review postsession reports for detailed evaluation and strategy formulation. The user 112 may further utilize the interface of the user device 112 to adjust configurable parameters of the system, such as weight factors used in the weighted combination or thresholds for triggering alerts.

[0084]

[0080] In one embodiment, the sensor unit 106 integrated within the apparel 104 may further be utilized to provide tactical insights for game strategy development. By analyzing positional and motion features of each collectively across players 102, the system may highlight formation compactness, inter-player coordination, and zone coverage efficiency. Such insights provide coaches and analysts with objective data to evaluate the effectiveness of formations, adjust player positioning, and refine strategic decisions in real time or during postsession reviews.

[0085]

[0081] In one embodiment, the smart wearable system 200 may be employed in the context of football (soccer) to evaluate both individual player performance and overall team dynamics. The sensor unit 106 integrated into the apparel 104 may capture physiological features such as heart rate and respiration, motion features such as sprint acceleration, deceleration, and jump count, and positional features such as player location, relative spacing, and adherence to tactical formations. The processing unit 208 may compute metrics such as formation stability and synchronization of defensive or offensive maneuvers. For example, the system may identify whether defensive players maintain compact formation spacing during opposition attacks or whether midfield players synchronize forward runs during counterattacks. In addition to tactical evaluation, the processing unit 208 may also be utilized for workload management of players 102, where continuous monitoring of physiological and motion features enables coaches to assess fatigue levels and make timely substitutions. Such data-driven substitutions not only help in maintaining player health but also contribute to optimizing team strategy during the course of a match. By generating real-time or post-session team performance scores, the system enables coaches to assess tactical execution, adjust player positioning, and refine match strategies based on objective data.

[0086]

[0082] In another embodiment, the smart wearable system 200 may be utilized in basketball to measure both physical workload and coordination during fast-paced gameplay. The sensor unit 106 may capture rapid changes in acceleration jumping impacts, and positional features reflecting player spacing and court coverage. The processing unit 208 may compute coordination metrics such as synchronization of player movements during offensive plays, balance of effort distribution across defensive roles, and inter-player coupling to assess the fluidity of ball movement and player rotations. For instance, the system may quantify how well the players 102 coordinate during a pick-and-roll action or maintain defensive balance when switching assignments. The team performance score generated in this context may provide actionable insights for improving training regimens, balancing player rotations, and enhancing tactical cohesion during competitive play.

[0087]

[0083] In yet another embodiment, the smart wearable system 200 may be applied in cricket to evaluate the performance of batsmen, bowlers, and fielders, both individually and collectively. The sensor unit 106 integrated into the apparel 104 may perform positional tracking to monitor field coverage by fielders, measure acceleration metrics during sprinting, and capture run-between-wickets speed for batsmen. For bowlers, the system may quantify workload parameters including overs bowled, delivery count, and arm stress as measured via the inertial measurement unit (IMU). The processing unit 208 may further evaluate coordination metrics among fielding units, such as synchronized positioning during catches or collaborative maneuvers during run-outs. In one embodiment, the system may also capture and analyze the reaction time of a batsman relative to the bowler he is facing, thereby providing additional insights into batting performance under varying match conditions. By aggregating these measurements, the system generates individual performance scores and a team performance score that reflect both workload distribution and tactical coordination specific to cricket.

[0088]

[0084] In one embodiment, the smart wearable system 200 may further be utilized for injury prediction. The system leverages a combination of physiological data, motion features, and EMG derived muscle activation maps to identify patterns indicative of fatigue, imbalance, or abnormal exertion. By continuously monitoring workload distribution and detecting asymmetrical or irregular activation across muscle groups, the system may generate predictive indicators of potential injury risk. These indicators may be communicated to the user 114 via the user device 112 in the form of alerts or reports, thereby enabling proactive intervention by coaches, trainers, or medical staff to adjust training loads, modify playing strategies, or implement recovery protocols. This injury prediction capability not only enhances player safety but also contributes to improved team performance by minimizing downtime due to preventable injuries.

[0085] Fig. 4 illustrates a flowchart depicting a method 400 for assessing team performance and determining the team performance score, in accordance with an embodiment of the present invention in accordance with an embodiment of the present invention. In this regard, each block may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the drawings. For example, two blocks shown in succession in Fig. 4 may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Any process descriptions or blocks in flow charts should be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process, and alternate implementations are included within the scope of the example embodiments in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved. In addition, the process descriptions orblocks in flow charts should be understood as representing decisions made by a hardware structure such as a state machine.

[0089]

[0086] At step 402, performance-related data of the plurality of players is captured via the plurality of sensors integrated with the apparel of each player. The plurality of sensors, collectively referred to as a sensor unit, may include physiological sensors, motion sensors, and positional sensors. The physiological sensors may capture signals such as heart rate, respiration rate, body temperature, or hydration level. The motion sensors may capture acceleration, deceleration, or jump impacts, while positional sensors may capture player location, formation adherence, and inter-player distances. The captured signals together provide a comprehensive representation of both individual and team activity during a sporting session.

[0090]

[0087] At step 404, the captured performance-related data is transmitted via the wireless communication module to the server over a communication network. The wireless communication module may employ one or more wireless protocols such as Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), Ultra- Wideband (UWB) or radio frequency (RF). In one embodiment, the transmission is performed directly to the base station or gateway connected to the server, whereas in other embodiment the transmission is carried out in a mesh network configuration, where multiple apparels cooperate to relay the data toward the server.

[0091]

[0088] At step 406, the processing unit within the server aggregates and temporally aligns the performance-related data received from the players. Since the players generate data asynchronously, temporal alignment ensures that each data point is mapped to the same time frame, thereby enabling meaningful comparisons across the team. Aggregation combines the individual data streams into a unified dataset suitable for further analysis.

[0092]

[0089] At step 408, the processing unit extracts the set of features from the aligned performance-related data. The set of features may include physiological features, motion features, and positional features. For example, physiological features may include metrics such as heart rate or respiration rate, motion features may include acceleration profiles or jump height, and positional features may include field coverage or relative spacing between players. These features serve as higher-level descriptors that transform raw sensor data into structured parameters relevant to performance analysis.

[0093]

[0090] At step 410, the processing unit normalizes the extracted features with respect to role-specific baselines associated with the players. The role-specific baselines may be predefined for different playing positions, dynamically adapted during gameplay, or derived from historical records stored in the memory. By performing normalization, the system ensures that the contribution of each player is evaluated fairly, considering the natural differences in physiological capacity or role responsibility.

[0094]

[0091] At step 412, the processing unit computes an individual performance score for each player based on the normalized features. The score provides a quantified measure of individual contribution and effort during the sporting activity. In one embodiment, the score may be continuously updated to provide real-time monitoring, while in another embodiment the scores may be aggregated at the end of a session to provide an overall summary of individual performance.

[0095]

[0092] At step 414, the processing unit computes one or more coordination metrics among the players. The coordination metrics may include formation stability, synchronization, balance of effort distribution, or inter-player coupling. The formation stability may be derived from positional data to determine how well players maintain their assigned positions. The synchronization may be derived by comparing timing of motion events across players. The balance of effort distribution may be computed by analyzing workload indices across the team, and inter-player coupling may be derived by measuring similarity or correlation of movement trajectories.

[0096]

[0093] At step 416, generates a team performance score based on the weighted combination of the individual performance scores and the one or more coordination metrics. The weights may be predefined or configurable based on the type of sport. In one embodiment, the team performance score may be computed in real time during gameplay, while in another embodiment it may be computed post-session to provide detailed analytical reports.

[0097] Technical Advancement and Economic Significance

[0098]

[0094] The smart apparel-based system for assessing team performance and determining team score disclosed in the present invention may have the following advantages over conventional art:

[0099] Provides a holistic evaluation of both individual player performance and overall team coordination.

[0100] Enables real-time monitoring of team performance through low-latency wireless data transmission.

[0101] Incorporates role-specific normalization, ensuring fair comparison across different player positions.

[0102] Generates a single unified team performance score, integrating physiological, motion, and positional data.

[0103] Supports synchronization and temporal alignment of multi-player data streams for accurate team analysis.

[0104] Computes coordination metrics such as formation stability, synchronization, and effort balance not addressed in existing systems.

[0105] Offers sport- specific adaptability by allowing customization of role baselines and weighting factors. Provides dual modes of operation, including real-time feedback during practice and post-session detailed reports.

[0106] Facilitates longitudinal performance tracking by storing data for trend analysis and historical comparisons.

[0107] Facilitates injury prevention by detecting early warning indicators such as asymmetrical muscle activation or excessive workload.

[0108] Assists in game strategy development by providing objective data on formation stability, inter-player coordination, and field coverage efficiency.

[0109]

[0095] Although implementations of a smart apparel-based system for assessing team performance and determining team score have been described in language specific to structural features and / or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of a smart apparel-based system for assessing team performance and determining team score.

[0110]

[0096] The invention has been described above with reference to numerous embodiments and specific examples. Many variations will suggest themselves to those skilled in this art in light of the above detailed description. All such obvious variations are within the full intended scope of the appended claims.

Claims

We Claim:

1. A smart wearable system (200) comprising: a plurality of sensors (106) integrated into an apparel (104) and configured to capture performance-related data of a plurality of players (102) during a sporting activity; a wireless communication module (206) communicatively coupled to the apparel (104), wherein the wireless communication module (206) is configured to transmit captured performance-related data to a server (110); a processing unit (208) within the server (110), communicatively coupled to the wireless communication module (206), wherein the processing unit (208) is configured to: aggregate and temporally align the captured performance -related data received from the wireless communication module (206); extract a set of features from aligned performance- related data; normalize extracted features with respect to role-specific baselines associated with the plurality of players (104); compute an individual performance score for each player (104) based on normalized features; compute one or more coordination metrics among the plurality of players (104); and generate a team performance score based on a weighted combination of the individual performance scores and the one or more coordination metrics.

2. The smart wearable system (200) as claimed in claim 1, wherein the plurality of sensors (106) comprises at least one of an electrocardiogram (ECG) sensor, electromyography (EMG) sensor, an inertial measurement unit, a positioning sensor, a pressure sensor, a temperature sensor, a hydration sensor, or a respiration sensor.

3. The smart wearable system (200) as claimed in claim 1, wherein the performance-related data comprises at least one of physiological data, motion data, or positional data.

4. The smart wearable system (200) as claimed in claim 1, wherein the apparel (104) further comprises a controller (202) configured to perform pre-processing of the captured performance-related data, wherein the pre-processing comprises at least one of noise filtering, timestamping of the data, and buffering of data packets.

5. The smart wearable system (200) as claimed in claim 1, wherein the wireless communication module (206) is configured to operate using at least one of Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (WiFi), Ultra-Wideband (UWB) and radio frequency (RF).

6. The smart wearable system (200) as claimed in claim 1, wherein the set of features comprises at least one of physiological features, motion features, and positional features.

7. The smart wearable system (200) as claimed in claim 1, wherein the one or more coordination metrics comprises at least one of formation stability, synchronization, relative benchmarking, balance of effort distribution, or inter-player coupling.

8. The smart wearable system as claimed in claim 1, wherein the server (110) further comprises a memory (210) communicatively coupled with the processing unit (208), wherein the memory (210) is configured to store program instructions executable by the processing unit, the performance-related data, the role-specific baselines, historical trend and log data, weight factors for score computation, the individual performance score and team performance score.

9. The smart wearable system (200) as claimed in claim 1, wherein the weights are configurable based on a type of sport.

10. The smart wearable system (200) as claimed in claim 1, wherein the smart wearable system (200) further comprises a user device (112) to display the team performance score, generate post-session reports including a timeline of the team performance score, individual performance scores, injury predictions, workload management and component breakdowns.

11. The smart wearable system (200) as claimed in claim 10, wherein the user device (112) is selected from the group comprising of a mobile phone, a tablet, a computer, a smartwatch, or a web-based dashboard.

12. The smart wearable system (200) as claimed in claim 1, wherein the processing unit (208) is further configured to provide injury prediction and workload management of the players (102).

13. The smart wearable system (200) as claimed in claim 1, wherein the apparel (104) further comprises a battery (204) configured to supply power to the plurality of sensors (106) and the controller (202).

14. A method (400) for generating a team performance score, the method (400) comprising: capturing, via a plurality of sensors (106), performance-related data of a plurality of players during a sporting activity; transmitting, via a wireless communication module (206), captured performance-related data to a server; aggregating and aligning, by a processing unit, the performance -related data received from the wireless communication module (206); extracting, by the processing unit (208), a set of features from aligned performance-related data; normalizing, by the processing unit (208), extracted features with respect to rolespecific baselines associated with the plurality of players; computing, by the processing unit (208), an individual performance score for each player based on normalized features; computing, by the processing unit (208), one or more coordination metrics among the plurality of players (102); and generating, by the processing unit (208), a team performance score based on a weighted combination of the individual performance scores and the one or more coordination metrics.

15. The method (400) as claimed in claim 14, wherein the plurality of sensors (106) comprises at least one of an electrocardiogram (ECG) sensor, electromyography (EMG)sensor, an inertial measurement unit, a positioning sensor, a pressure sensor, a temperature sensor, a hydration sensor, or a respiration sensor.

16. The method (400) as claimed in claim 14, wherein the performance-related data comprises at least one of physiological data, motion data, or positional data.

17. The method (400) as claimed in claim 14, wherein the plurality of sensors (106) is further configured to perform pre-processing of the captured performance-related data, wherein the pre-processing comprises at least one of noise filtering, timestamping of the data, and buffering of data packets.

18. The method (400) as claimed in claim 14, wherein the wireless communication module (206) is configured to operate using at least one of Bluetooth Low Energy (BLE), Adaptive Network Topology Plus (ANT+), Wireless Fidelity (Wi-Fi), Ultra-Wideband (UWB), and radio frequency (RF).

19. The method (400) as claimed in claim 14, wherein the set of features comprises at least one of physiological features, motion features, and positional features.

20. The method (400) as claimed in claim 14, wherein the one or more coordination metrics comprises at least one of formation stability, synchronization, relative benchmarking, balance of effort distribution, or inter-player coupling.

21. The method (400) as claimed in claim 14, wherein the server further comprising: a memory (210) communicatively coupled with the processing unit (208), wherein the memory (210) is configured to store program instructions executable by the processing unit (208), the performance-related data, the role-specific baselines, historical trend and log data, weight factors for score computation, the individual performance score and team performance score.

22. The method (400) as claimed in claim 14, wherein the weights are configurable based on a type of sport.

23. The method (400) as claimed in claim 14, wherein the smart wearable system (200) further comprising:a user device ( 112) to display the team performance score, generate post-session reports including a timeline of the team performance score, individual performance scores, injury prediction, workload management and component breakdowns.

24. The method (400) as claimed in claim 23, wherein the user device (112) is selected from the group comprising of a mobile phone, a tablet, a computer, a smartwatch, or a web- based dashboard.

25. The method (400) as claimed in claim 14, wherein the processor (208) further configured to provide injury prediction and workload management of the players (102).

26. The method (400) as claimed in claim 14, wherein the apparel (104) further comprising: a battery (204) configured to supply power to the plurality of sensors (106) and the controller (202).

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